ICORES 2012 Abstracts


Area 1 - Methodologies and Technologies

Full Papers
Paper Nr: 28
Title:

SYMMETRY BREAKING CONSTRAINTS FOR THE PROBLEM OF PACKING EQUAL CIRCLES IN A SQUARE

Authors:

Alberto Costa and Ider Tseveendorj

Abstract: The Packing Equal Circles in a Square (PECS) problem is a nonconvex nonlinear optimization problem which involves a high degree of symmetry. The Branch-and-Bound algorithms work bad due to the presence of symmetric optima, because the Branch-and-Bound tree becomes large, and the time to reach the leaves (i.e., the optimal solutions) increases. In this paper, we introduce some inequalities which reduce the symmetry of the problem, and we present some numerical results.

Paper Nr: 44
Title:

BUSINESS PROCESS ENTERPRISE MODEL - Operations Research for Managing Business Process Communication and Performance

Authors:

Yves Caseau

Abstract: This paper presents a computational model of a generic enterprise (BPEM, which stands for Business Process Enterprise Model), based upon the core concept of business process. BPEM may be seen as a bridge between two worlds of “Enterprise Models”, the world of mathematical models, formal and fully operational for optimization purposes and the world of conceptual models (boxes & arrows type) for management science, for reasoning and communicating about what a company is. Our model was built as the minimal and most elegant model that is detailed enough to investigate difficult management science issues such as the influence of hierarchical organization on performance, the optimal usage of various communication channels or the benefits of lean-management-style control of processes. BPEM is organized around four concepts: business processes, capabilities that encapsulate resource management, hierarchical and transverse management organization, as well as information flows that are required to run business processes.

Paper Nr: 50
Title:

A STRATEGIC SIMULATION TOOL FOR CAPABILITY-BASED JOINT FORCE STRUCTURE ANALYSIS

Authors:

Cheryl Eisler and Dave Allen

Abstract: This paper describes a stochastic discrete event simulation model for scheduling of joint military force structures. The model employs capability-based methods to link scenario requirements to force structure assets. Assignment of assets to scenarios is designed to attempt to mimic the decisions of a military scheduler. Force structure performance is evaluated based on how well and how often scenario capability requirements are met. The model output permits options analysis, capability gap analysis, determination of optimal force structure composition, and evaluation of force structure performance in the face of changing requirements and policies (such as readiness and sustainment, operations tempo, and personnel tempo constraints).

Paper Nr: 57
Title:

IMPACT OF BLOCKING WHEN CUSTOMERS OF DIFFERENT CLASSES ARE ACCOMMODATED IN ONE COMMON QUEUE

Authors:

Herwig Bruneel, Willem Mélange, Bart Steyaert, Dieter Claeys and Joris Walraevens

Abstract: In this paper, situations are investigated where customers requiring different types of service, each provided by distinct servers, are accommodated in one common queue. In such scenarios, customers of one class (i.e., requiring a given type of service) may be hindered (“blocked”) by customers of other classes. For instance, if a road or a highway is split in two or more subroads leading to different destinations, cars on that road heading for destination A may be hindered or even blocked by cars heading for destination B, even when the subroad leading to destination A is free, simply because they have to queue in first-come-first-served (FCFS) order on the main road. The purpose of this paper is to study the effect of blocking. We therefore develop a discrete-time queueing model and establish performance measures related to the number of waiting customers. Based on the obtained results, we demonstrate that clustering of arrivals according to class pronounces the negative impact of blocking. We believe that the impact of class clustering on blocking has been largely overlooked in the regular operations research and queueing literature.

Paper Nr: 80
Title:

COMPUTING VALID INEQUALITIES FOR GENERAL INTEGER PROGRAMS USING AN EXTENSION OF MAXIMAL DUAL FEASIBLE FUNCTIONS TO NEGATIVE ARGUMENTS

Authors:

Jürgen Rietz, Cláudio Alves, J. M. Valério de Carvalho and François Clautiaux

Abstract: Dual feasible functions (DFFs) were used with much success to compute bounds for several combinatorial optimization problems and to derive valid inequalities for some linear integer programs. A major limitation of these functions is that their domain remains restricted to the set of positive arguments. To tackle more general linear integer problems, the extension of DFFs to negative arguments is essential. In this paper, we show how these functions can be generalized to this case. We explore the properties required for DFFs with negative arguments to be maximal, we analyze additional properties of these DFFs, we prove that many classical maximal DFFs cannot be extended in this way, and we present some non-trivial examples.

Paper Nr: 89
Title:

APPLYING CASE-BASED REASONING FOR IDENTIFYING THE NEGOTIATION PROFILE OF ELECTRONIC NEGOTIATION SYSTEM USERS

Authors:

Jakub Brzostowski and Tomasz Wachowicz

Abstract: In this paper we analyze the problem of identifying the negotiation profile of the electronic negotiation system users. Usually such a profile is identified by means of the specific questionnaire (e.g. the Thomas-Kilmann questionnaire), however it requires from the negotiator answering many troublesome questions which is tiring and may lead to unreliable results. On the other hand many behavioural and psychological studies confirm that there is a set of demographical and sociological characteristics that influence the human general behaviour. Deriving from these studies we try to determine such a profile by analyzing the general information provided by the pre-negotiation questionnaire the users fill while creating their negotiation accounts. Having the historical data of Inspire negotiation system we try to find links between a set of the data that describes the negotiators demographical features and their final negotiation profile using the notion of Gilboa and Schmeidler case-based reasoning (CBR). To determine all the parameters required for the case-based reasoning the statistical correspondence analysis on the set of the historical data is conducted in advance. The results of CBR-based profile identification are also presented and discussed.

Paper Nr: 96
Title:

SYNAPTIC TRANSMISSION AND FOKKER-PLANCK EQUATION

Authors:

Elso Drigo Filho and Marcelo Araujo

Abstract: An important neurologic process consists in a time dependent transmission of the electric signal between neurons. The description of such signal is the objective of this work. In this way, the Fokker-Planck equation with a term of control which depends on time is used. The applied force is characterized by the existence of a barrier that increases with time and reduces the diffusion of particles. The solution of the equation is obtained by an ansatz that satisfies the initial conditions of the problem. Numerical examples of the time evolution of the found solutions are analyzed by calculating the escape rate and the time necessary to across the barrier for different values of diffusion constant.

Paper Nr: 110
Title:

BRKGA ADAPTED TO MULTIOBJECTIVE UNIT COMMITMENT - Solving Pareto Frontier for UC Multiobjective Problem using BRKGA SPEA2 NPGA and NSGA II Techniques

Authors:

Luís A. C. Roque, Dalila B. M. M. Fontes and Fernando A. C. C. Fontes

Abstract: The environmental concerns are having a significant impact on the operation of power systems. The traditional Unit Commitment problem, which to minimizes the fuel cost is inadequate when environmental emissions are also considered in the operation of power plants. This paper presents a Biased Random Key Genetic Algorithm (BRKGA) approach combined with non-dominated sorting procedure to find solutions for the unit commitment multiobjective optimization problem. In the first stage, the BRKGA solutions are encoded by using random keys, which are represented as vectors of real numbers in the interval [0,1]. In the subsequent stage, a non-dominated sorting procedure similar to NSGA II is employed to approximate the set of Pareto solution through an evolutionary optimization process. The GA proposed is a variant of the random key genetic algorithm, since bias is introduced in the parent selection procedure, as well as, in the crossover strategy. Test results with the existent benchmark systems of 10 units and 24 hours scheduling horizon are presented. The comparison of the obtained results with those of other Unit Commitment (UC) multiobjective optimization methods reveal the effectiveness of the proposed method.

Paper Nr: 132
Title:

CONTINUOUS-TIME REVENUE MANAGEMENT IN CARPARKS

Authors:

A. Papayiannis, P. Johnson, D. Yumashev, S. Howell, N. Proudlove and P. Duck

Abstract: In this paper, we study optimal revenue management applied to carparks, with primary objective to maximize revenues under a continuous-time framework. We develop a stochastic discrete-time model and propose a rejection algorithm that makes optimal decisions (accept/reject) according to the future expected revenues generated and on the opportunity cost that arises before each sale. For this aspect of the problem, a Monte Carlo approach is used to derive optimal rejection policies. We then extend this approach to show that there exists an equivalent continuous-time methodology that yields to a partial differential equation (PDE). The nature of the PDE, as opposed to theMonte Carlo approach, generates the rejection policies quicker and causes the optimal surfaces to be significantly smoother. However, because the solution to the PDE is considered not to solve the ‘full’ problem, we propose an approach to generate optimal revenues using the discrete-time model by exploiting the information coming from the PDE. We give a worked example of how to generate near-optimal revenues with an order of magnitude decrease in computation speed.

Paper Nr: 152
Title:

A FORWARD-BACKWARD ALGORITHM FOR STOCHASTIC CONTROL PROBLEMS - Using the Stochastic Maximum Principle as an Alternative to Dynamic Programming

Authors:

Stephan E. Ludwig, Justin A. Sirignano, Ruojun Huang and George Papanicolaou

Abstract: An algorithm for solving continuous-time stochastic optimal control problems is presented. The numerical scheme is based on the stochastic maximum principle (SMP) as an alternative to the widely studied dynamic programming principle (DDP). By using the SMP, (Peng, 1990) obtained a system of coupled forward-backward stochastic differential equations (FBSDE) with an external optimality condition. We extend the numerical scheme of (Delarue and Menozzi, 2006) by a Newton-Raphson method to solve the FBSDE system and the optimality condition simultaneously. As far as the authors are aware, this is the first fully explicit numerical scheme for the solution of optimal control problems through the solution of the corresponding extended FBSDE system. We discuss possible numerical advantages to the DDP approach and consider an optimal investment-consumption problem as an example.

Short Papers
Paper Nr: 9
Title:

ECONOMIC DESIGN OF MEWMA VSSI CONTROL CHARTS FOR MULTIATTRIBUTE PROCESSES

Authors:

Seyed Taghi Akhavan Niaki and Paravaneh Jahani

Abstract: In this research, a new methodology is developed to economically design a multivariate exponentially weighted moving average (MEWMA) control chart for multiattribute processes. The optimum design parameters of the chart, i.e., the sample size, the sampling interval, and the warning/action limit coefficients, are obtained using a genetic algorithm to minimize the expected total cost per hour. A sensitivity analysis has also been carried out to investigate the effects of the cost and model parameters on the solutions obtained.

Paper Nr: 12
Title:

AGGREGATION OF STAKEHOLDER PREFERENCES IN SUSTAINABLE FOREST MANAGEMENT USING AHP

Authors:

C. Maroto, M. Segura, C. Ginestar, J. Uriol and B. Segura

Abstract: The Analytic Hierarchy Process (AHP) is the most often applied approach to modelling strategic forest management problems. When dealing with Multiple Criteria Decision Making, AHP allows one to take social, economic and environmental criteria of sustainability concept, as well as public participation, into account. We carried out a workshop to validate a decision hierarchy for Sustainable Management in Mediterranean forests, as well as two surveys to elicit social priorities. Stakeholder and expert judgments were integrated using the geometric mean to obtain group preferences. We applied this method to develop empirical research into sustainable forest management in a Mediterranean region, where the environmental and social services of the forest are more important than the economic ones. We quantified weights of criteria, objectives and management strategy priorities and discuss the obtained results.

Paper Nr: 21
Title:

PRICE SKIMMING STRATEGY FOR NEW PRODUCT DEVELOPMENT

Authors:

Hassan Shavandi and Ata G. Zare

Abstract: This article presents a new model for pricing a new product considering skimming pricing strategy in the presence of the competition. We consider two periods for price setting including skimming and economy period. The problem is deciding on a skimming price as well as an economy price in order to maximize the total profit. The derived model is a non-linear programming model and we analyzed the structure and properties of optimal solution to develop a solution method. Analytical results as well as managerial insights are presented by mathematical analysis and numerical analysis.

Paper Nr: 40
Title:

SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models

Authors:

Bindu Narayan, Deepak Ravindran, Picton Sue and Jayant Das Pattnaik

Abstract: Sales pipeline metaphorically is a pipe through which the opportunities pass on the way to becoming a sale. As the opportunity progresses through the pipe the likelihood of becoming a sale increases. Predicting the sales pipeline is very critical. Accurately predicting the sales pipeline is essential in planning future costs and capacity requirements. Since the sales pipeline is in itself a subjective prediction made by sales reps, predicting the pipeline essentially becomes a problem of predicting a prediction. Most managers do this by solely depending on their sales representatives perception on which business will close. A prediction model was developed using time series modeling to predict the next quarter sales pipeline. The uniqueness of the model is that, it captures two different types of co-existing seasonlaities. A predictive model was created which is refreshed weekly with actual pipeline numbers and is successfully deployed within business.

Paper Nr: 43
Title:

A TWO-PLAYER MODEL FOR THE SIMULTANEOUS LOCATION OF FRANCHISING SERVICES WITH PREFERENTIAL RIGHTS

Authors:

Pedro Godinho and Joana Dias

Abstract: We consider the discrete location problems faced by two decision-makers, franchisees, that will have to simultaneously decide where to locate their own services (unsure about the decisions of one another). All services compete among themselves. At most one service can be located at each potential location. We consider that one of the decision-makers has preferential rights meaning that if both decision makers are interested in the same location, only to this decision-maker will be given the permission to open the service. We present a mathematical formulation and some conclusions based on computational results.

Paper Nr: 46
Title:

BI-LEVEL CLUSTERING IN TELECOMMUNICATION FRAUD

Authors:

Luis Pedro Mendes, Joana Dias and Pedro Godinho

Abstract: In this paper we describe a fraud detection clustering algorithm applied to the telecom industry. This is an ongoing work that is being developed in collaboration with a leading telecom operator. The choice of clustering algorithms is justified by the need of identifying clients’ abnormal behaviors through the analysis of huge amounts of data. We propose a novel bi-level clustering methodology, where the first level is concerned with the clustering of transactional data and the second level gathers data from the first phase, along with other information, to build high-level clusters.

Paper Nr: 99
Title:

SOLVING THE 3D CONTAINER SHIP LOADING PLANNING PROBLEM BY REPRESENTATION BY RULES AND BEAM SEARCH

Authors:

Anibal Tavares de Azevedo, Cassilda Maria Ribeiro, Galeno José de Sena, Antônio Augusto Chaves, Luis Leduíno Salles Neto and Antônio Carlos Moretti

Abstract: This paper formulates the 3D Container ship Loading Planning Problem (3D CLPP) and also proposes a new and compact representation to efficiently solve it. Containers on board a Container ship are placed in vertical stacks, located in different sections. The only way to access the containers is through the top of the stack. In order to unload a container at a given port j, it is necessary to remove the container whose destination is the port j+1, because it is located above the container we want to download. This operation is called “shifting”. A ship container carrying cargo to several ports may require a large number of shifting operations. These operations spend a lot of time and cost and can be avoided by using efficient stowage planning. The key objective of the stowage planning is to minimize the number of container movements and also the ship instability. The binary formulation of this problem is properly described and also an alternative formulation called representation by rules is proposed. A Beam Search is combined with representation by rules to solve the 3D CLPP in manner that ensures that every solution analyzed in the optimization process is compact and feasible.

Paper Nr: 100
Title:

STUDY ON QUEUING BEHAVIOR IN A MULTICHANNEL SERVICE FACILITY USING EXPERIMENTAL METHODS

Authors:

Karthik Sankaranarayanan, Carlos Arturo Delgado, Erik R. Larsen and Ann van Ackere

Abstract: In this paper we show how through a simple experimental setup we can study decision making in a multi-channel service facility. An agent based queuing framework is used to design this experimental study and we illustrate how the experiment was set up to collect data from human subjects who take the role of a virtual agent. This experimental data helps us to validate the proposed agent based framework, compare decision making strategies, and analyse the effects of behavioural parameters on decision making.

Paper Nr: 108
Title:

TERMINATION OF SIMULATED ANNEALING ALGORITHM SOLVING SEMI-SUPERVISED LINEAR SVMS PROBLEMS

Authors:

Vaida Bartkute-Norkuniene

Abstract: In creating heuristic search algorithms one has to deal with the practical problem of terminating and optimality testing. To solve these problems, we can use information gained from the set of the best function values (order statistics) provided during optimization. In this paper, we consider the application of order statistics to establish the optimality in heuristic optimization algorithms and to stop the Simulated Annealing algorithm when the confidence interval of the minimum becomes less than admissible value. The accuracy of the solution achieved during optimization and the termination criterion of the algorithm are introduced in a statistical way. We build a method for the estimation of confidence intervals of the minimum using order statistics, which is implemented for optimality testing and terminating in Simulated Annealing algorithm. A termination criterion - length of the confidence interval of the extreme value of the objective function - is introduced. The efficiency of this approach is discussed using the results of computer modelling. One test function and two semi-supervised SVMs linear classification problems illustrate the applicability of the method proposed.

Paper Nr: 109
Title:

SOLVING THE RCPSP WITH AN EVOLUTIONARY ALGORITHM BASED ON INSTANCE INFORMATION

Authors:

José António Oliveira, Luís Dias and Guilherme Pereira

Abstract: The Resource Constrained Project Scheduling Problem (RCPSP) is NP-hard thus justifying the use meta-heuristics for its solution. This paper presents an evolutionary algorithm developed for the RCPSP problem. This evolutionary algorithm uses an alphabet based on random keys that makes easier its implementation while solving combinatorial optimization problems. Random keys allow the use of conventional genetic operators, what makes easier the adaptation of the evolutionary algorithm to new problems. To improve the method's performance, this evolutionary algorithm uses an initial population that is generated considering the information available for the instance. This paper studies the impact of using that information in the initial population. The computational experiments presented compare two types of initial population - the conventional one (generated randomly) and this new approach that considers the information of the instance.

Paper Nr: 111
Title:

A COLUMN GENERATION APPROACH FOR THE BI-OBJECTIVE MAX-MIN KNAPSACK PROBLEM

Authors:

Cláudio Alves, Raid Mansi, Telmo Pinto and José Valério Carvalho

Abstract: In this paper, we propose a new approach to compute strong lower and upper bounds for the bi-objective max-min knapsack problem. It relies on a reformulation of the problem using the Dantzig-Wolfe decomposition principle. The model resulting from this decomposition is an exponential integer linear program whose linear relaxation can be solved efficiently using a column generation procedure. We describe the details of this decomposition and the related column generation algorithm. To evaluate the performance of our approach, we conducted a set of comparative computational experiments on instances obtained with a generator described in the literature. The results obtained show that our approach outperforms other state-of-the-art methods.

Paper Nr: 112
Title:

DEVELOPMENT OF AN OPTIMIZATION MODEL FOR IMAGE COLLECTION PLANNING

Authors:

Jinbong Jang, Jiwoong Choi and In-Chan Choi

Abstract: Customer service requests for satellite-based image collection rapidly grow in Korea as the number of available satellites increases. The customer requests must meet their due dates under several complicating conditions, such as memory capacity limits, weather conditions, role tilts and segment conflict resolutions. In this paper, we address this problem by presenting a mixed-integer program model and propose an investigative solution approach that handles millions of segment conflict resolution constraints. The proposed approach would reduce the model size to improve its solvability by utilizing a new redundancy checking pre-processing technique.

Paper Nr: 119
Title:

EVALUATING VEHICLE ROUTING PROBLEMS WITH SUSTAINABILITY COSTS

Authors:

Ignacio Eguia, Jesus Racero and Fernando Guerrero

Abstract: In this paper, we study the road freight transportation activities, which are significant sources of air pollution, noise and greenhouse gas emissions, with the former known to have harmful effects on human health and the latter, responsible for global warming. Specifically, an extension of the classical Capacitated Vehicle Routing Problem is presented, including realistic assumptions (Time Windows, Backhauls and Heterogeneous Fleet with different vehicles and fuel types). The decisions are aimed at the selection of vehicle and fuel types, the scheduling of deliveries and pick-up processes and the consolidation of freight flows. The classical objective functions of minimizing the total travel distance or the internal costs (driver, fuel or maintenance) are extended to other sustainable measures: the amount of air pollution and greenhouse gas emissions, the energy consumption and their costs. A mathematical model is described and an illustrative example is performed.

Paper Nr: 125
Title:

STRATEGIES TO MODEL SCHEDULING DECISIONS TO PLAN THE SOFT DRINK PRODUCTION PROCESS

Authors:

Socorro Rangel and Michelli Maldonado

Abstract: In this paper we present a mixed integer model that integrates lot sizing and lot scheduling decisions for the production planning of a soft drink company. The main contribution of the paper is to present a model that differ from others in the literature for the constraints related to the scheduling decisions. The proposed strategy is compared to other strategies presented in the literature.

Paper Nr: 141
Title:

ENTERPRISE NETWORK REDESIGN THROUGH SERVER CONSOLIDATION

Authors:

Abeer Al-Fadhel, Paulvanna N. Marimuthu and Sami J. Habib

Abstract: In this paper, we have explored the utilization of existing servers within an enterprise information network (EIN), and we have proposed redesign operations on servers to identify and remove the low-utilized servers. The low-utilized servers consume unnecessary power and increase the operational and maintenance cost. The removal of low-utilized server is viewed as an EIN redesign problem, which removes the low-utilized servers within the EIN and re-distributes the clients of the purged servers to the remaining servers, thereby reducing a portion of expenditure on maintenance and operation. We have proposed three approaches on distributing the clients of removed servers and the approaches are; single server pure random distribution, selective distribution and multiple servers pure random distribution. We have employed Simulated Annealing to search for best possible random server/servers in order to distribute the workload of the removed server, thereby improving the utilization of the remaining servers. The simulation results for a given EIN with 10 servers and 25 clusters show that our proposed server consolidation approaches improve the initial average server utilization of around 25% to 60%, 68.5%, and 90% respectively in the proposed three methods.

Posters
Paper Nr: 39
Title:

APPROXIMATE SOLUTIONS FOR SOME ADVANCED MULTISERVER RETRIAL QUEUES

Authors:

Yang Woo Shin and Dug Hee Moon

Abstract: Retrial queues have been widely used for modelling many practical problems arising in computer and communication systems. It has been known to be difficult problems to develop a numerical algorithm or an approximate solution for advanced multiserver retrial queues such as the models with phase type distribution of retrial time, impatient customers governed by a general persistence function and multiclass of customers. Recently, we have developed an approximation method based on the approach in Fredericks and Reisner (1979) with some modifications for the advanced systems described above. In this paper, we introduce the approximation results developed recently.

Paper Nr: 49
Title:

MAXIMUM LIKELIHOOD ESTIMATION OF MULTIVARIATE SKEW T-DISTRIBUTION

Authors:

Leonidas Sakalauskas and Ingrida Vaiciulyte

Abstract: The present paper describes the Monte – Carlo Markov Chain (MCMC) method for estimation of skew t – distribution. The density of skew t – distribution is obtained through a multivariate integral, using representation of skew t – distribution by a mixture of multivariate skew – normal distribution with the covariance matrix, depending on the parameter, distributed according to the inverse – gamma distribution. Next, the MCMC procedure is constructed for recurrent estimation of skew t – distribution, following the maximum likelihood method, where the Monte – Carlo sample size is regulated to ensure the convergence and to decrease the total amount of Monte – Carlo trials, required for estimation. The confidence intervals of Monte – Carlo estimators are introduced because of their asymptotic normality. The termination rule is also implemented by testing statistical hypotheses on an insignificant change of estimates in two steps of the procedure.

Paper Nr: 54
Title:

INTEGRATED PRODUCTION AND MAINTENANCE PLANNING - Modeling Corrective Maintenance

Authors:

Veronique Limère, Jasper Deschacht and El-Houssaine Aghezzaf

Abstract: We are given a production system composed of several parallel machines subject to random failures. A set of items are to be produced in lots on these machines. To prevent failure production system must be maintained. We assume that these maintenance actions have an effect on the available production capacity of each machine. The objective is to generate an integrated production and preventive maintenance plan that optimizes the total costs for the system. In this paper we first discuss an existing mathematical formulation of the problem and then propose an extension and illustrate it with an example.

Paper Nr: 61
Title:

ECONOMIC-PROBABILISTIC MODEL FOR RISK ANALYSIS IN PROJECTS

Authors:

Rogério Feroldi Miorando, José Luis Duarte Ribeiro, Maria A. C. Tinoco and Carla Schwengber ten Caten

Abstract: This paper presents an economic-probabilistic model to conduct risk analysis in projects. The model integrates risk and economic project analysis by quantifying both value and probability of occurrence of potential cash flow deviations, thus resulting in an economic-probabilistic analysis of the expected returns. The model allows calculating risk-adjusted values for cash flow groups and projecting net present value through stochastic simulation. As a result, the model provides both the risk-adjusted project economic return with the associated probability distribution to its NPV and the variability that each risk factor generates in the project return.

Paper Nr: 67
Title:

A TEXT CLASSIFICATION METHOD BASED ON LATENT TOPICS

Authors:

Yanshan Wang and In-Chan Choi

Abstract: Latent Dirichlet Allocation (LDA) is a generative model, which exhibits superiority over other topic modelling algorithms on latent topics of text data. Indexing by LDA is a new method in the context of LDA to provide a new definition of document probability vectors that can be applied as feature vectors. In this paper, we propose a joint process of text classification that combines DBSCAN, indexing with LDA and Support Vector Machine (SVM). DBSCAN algorithm is applied as a pre-processing for LDA to determine the number of topics, and then LDA document indexing features are employed for text classifier SVM.

Paper Nr: 113
Title:

A SERVICE-ORIENTED APPROACH TO EFFICIENT DECISION SUPPORT

Authors:

Goran Mihelcic, Bo Hu and Stefan Pickl

Abstract: Historically grown IT-landscapes in modern business, often referred to as ‘legacy’ systems or ‘accidental architectures’, can have a strong impact on the efficiency of decision support processes. Caused by a high level of separation of essential software applications, crucial information needed may often be difficult and time consuming to retrieve. The authors show one approach of how distributed business-critical software applications can be integrated using the service oriented architecture paradigm. The implementation of webservices can increase the flexibility and integrity of decision support processes. The authors demonstrate their approach in the context of a participatory system dynamics modelling application.

Paper Nr: 118
Title:

OPTIMIZATION TOOLS ADRESSING FUZZY UNCERTAINTY AT POWER FLOWS

Authors:

Eduardo M. Gouveia and Paulo Moisés Costa

Abstract: Power flow studies use computational tools for the planning and operation of electrical power systems purposes. The deterministic model is the most commonly used load flow approach. In this model, the input data and the results are crisp values. Therefore, to account for uncertainties, the most common approach used is the definition of scenarios, which are characterized by crisp values. This is an impractical way to solve the problem of the uncertainty in the data. A more practical way to lead with the uncertainties is the use of probabilistic power flows. On such approach, the uncertainties are modelled through the use of probability density functions (pdf). However, that approach may be inappropriate, namely when there is no available historical data in order to construct the pdf. On such cases, the fuzzy power flows (FPF) is an interesting alternative. In this paper, a methodology named Symmetric Fuzzy Power Flow is used. That methodology uses optimization models to solve power flow problems considering the uncertainty treated as fuzzy numbers. A comparison between the proposed methodology and the classic ones is also provided.

Paper Nr: 140
Title:

THE ANALYTICAL HIERARCHY PROCESS (AHP) APPROACH TO MODELLING CORPORATE CLIMATE CHANGE RESPONSE

Authors:

Muriel Chinoda and Jan Kruger

Abstract: The heightened risks and opportunities posed by climate change call for increased attention by business executives to employ creative and rigorous methodology in generating strategic response options. Because climate change is influenced by an assortment of multiple and interdependent variables, the search for solutions to this complex challenge ought to be a multi-dimensional trade-off seamlessly integrated into corporate strategy. Analytical hierarchy process (AHP)’s ability to hierarchically structure complexity into homogeneous clusters of factors renders it as an appropriate decision support tool allowing for the interconnectedness of climate change systems, the constraints in time, knowledge and computational abilities that humans face. This paper presents a conceptual view of the approach, exploring key aspects of how AHP assists in deriving a climate change model for businesses.

Area 2 - Applications

Full Papers
Paper Nr: 15
Title:

AN EXACT ALGORITHM FOR THE CLOSE ENOUGH TRAVELING SALESMAN PROBLEM WITH ARC COVERING CONSTRAINTS

Authors:

Minh Hoang Ha, Nathalie Bostel, André Langevin and Louis-Martin Rousseau

Abstract: In this paper, we consider a problem still seldom studied in the literature, the Close Enough Traveling Salesman problem with covering constraints on the arcs. This problem arises in the context of utility companies that use automated meter reading (AMR) with radio frequency identification (RFID) technology to read meters from a distance. The contribution of this paper is to introduce a new mathematical formulation and to propose a first exact algorithm for this problem. Computational results show that our algorithm is capable of solving to optimality instances of realistic size, such as those introduced in (Golden et al., 2008), with 1000 arcs and 9000 customers in less than 2 hours.

Paper Nr: 27
Title:

COPING WITH LONG TERM MODEL RISK IN MARKET RISK MODELS

Authors:

Manuela Spangler and Ralf Werner

Abstract: The recent financial crisis has shown that most market risk models – even if they deliver sufficiently accurate risk figures over short time horizons – are not able to provide reliable forecasts for risk figures over longer time horizons like three, twelve or 36 months, which are the basis for both limit management and economic capital planning. As a potential remedy the concept of potential future market risk can be used to deal with such long term model risks in market risk measurement. Based on a toy example we will outline how this concept can be applied for new business planning or for limit setting and capital buffer definitions.

Paper Nr: 31
Title:

HYBRID COLUMN GENERATION-BASED APPROACH FOR VRP WITH SIMULTANEOUS DISTRIBUTION, COLLECTION, PICKUP-AND-DELIVERY AND REAL-WORLD SIDE CONSTRAINTS

Authors:

Lorenzo Ruinelli, Matteo Salani and Luca Maria Gambardella

Abstract: We present an optimization algorithm that hybridizes heuristic and exact methods to solve the problem of a real-world distribution company. Our algorithm combines three existing optimization techniques (Ant Colony Optimization, Column Generation and Mixed Integer Programming). Standard Column Generation is improved with an incremental search technique able to speed up the entire process. We present computational results on 14 real-world instances obtained from our industrial partner. Finally, we compare the solutions obtained by our algorithm against those currently computed by the route planning office of our industrial partner. Beside cost savings, we asses the reliability of our approach in terms of computational time and quality.

Paper Nr: 48
Title:

STOCHASTIC SHORTEST PATH PROBLEM WITH UNCERTAIN DELAYS

Authors:

Jianqiang Cheng, Stefanie Kosuch and Abdel Lisser

Abstract: This paper considers a stochastic version of the shortest path problem, the Stochastic Shortest Path Problem with Delay Excess Penalty on directed, acyclic graphs. In this model, the arc costs are deterministic, while each arc has a random delay, assumed normally distributed. A penalty occurs when the given delay constraint is not satisfied. The objective is to minimize the sum of the path cost and the expected path delay penalty. In order to solve the model, a Stochastic Projected Gradient method within a branch-and-bound framework is proposed and numerical examples are given to illustrate its effectiveness. We also show that, within given assumptions, the Stochastic Shortest Path Problem with Delay Excess Penalty can be reduced to the classic shortest path problem.

Paper Nr: 66
Title:

THE PRIZE-COLLECTING VEHICLE ROUTING PROBLEM WITH NON-LINEAR COST - Integration of Subcontractors into Route Design of Small Package Shippers

Authors:

Andreas Stenger

Abstract: In this paper, we propose a new routing problem to model a highly relevant planning problem in small package shipping. The problem, called Prize-Collecting Vehicle Routing Problem with Non-Linear cost (PCVRPNL), allows for each customer the choice of being serviced by a vehicle of the private fleet or being outsourced to a subcontractor. A lower bound on the total customer demand serviced by the private fleet ensures a constant capacity utilization. The subcontracting costs follow a non-linear function representing the discount given by a subcontractor if larger amounts of packages are assigned. To solve the NP-hard problem, we propose a Variable Neighborhood Search algorithm. In numerical studies performed on benchmark instances adapted from classical VRP, we demonstrate the strong performance of our algorithm and study the effect of different cost functions on the routing solution.

Paper Nr: 72
Title:

A COOPERATIVE MODEL FOR MULTI-CLASS PEER-TO-PEER STREAMING NETWORKS

Authors:

Pablo Romero, María Elisa Bertinat, Darío Padula, Pablo Rodríguez-Bocca and Franco Robledo Amoza

Abstract: Peer-to-peer networks are strongly based on cooperation. The users, called peers, communicate basically in a three-level based policy. In the first one, peers discover others interested in the same content, and is called swarm selection strategy (or swarming). Then, peers must select the best ones to cooperate, what is called peer selection strategy. Finally, peers cooperate sending pieces to each other, and the planning must attend the piece selection strategy. In this paper we propose an extension of a simple model based on cooperation for peer-to-peer video streaming networks. We assume that the swarming classifies peers according to their bandwidth. In this model we meet both the peer and the piece selection strategies, for simplified scenarios. The aim is to design network policies in order to achieve the highest continuity of video reproduction when peers reach a stationary state. We show that under full knowledge, the network can scale even under free-riding effects. At the same time, we provide theoretical results that reveal Rarest First has a poor performance in comparison with other techniques. Finally, we analyze the scalability in a worst-case scenario when a variable amount of special peers are included in the network.

Paper Nr: 73
Title:

EFFICIENT WASTE COLLECTION BY MEANS OF ASSIGNMENT PROBLEMS

Authors:

Kostanca Katragjini, Federico Perea and Rubén Ruiz

Abstract: This paper studies a municipal waste collection problem, whose ultimate goal is to find an assignment of containers to service days and posterior routing so that the total distance covered by the waste collection trucks is minimized. Due to the complexity of this problem, we divide it into several subproblems. The focus of this paper is on the first problem, in which it must be decided which containers must be collected on each service day so that the containers collected on the same day are as close to each other as possible. In a second phase (out of the scope of this paper) the routes followed by the collection vehicles at each service day are optimized. Such separation of the problem is needed as a result of the sheer size and complexity of the real setting. Despite this separation into smaller subproblems, efficient procedures must be designed in order to solve real-sized instances. A computational experience over a number of instances shows the applicability of our methods.

Paper Nr: 83
Title:

INVENTORY ALLOCATION FOR ONLINE GRAPHICAL DISPLAY ADVERTISING USING MULTI-OBJECTIVE OPTIMIZATION

Authors:

Jian Yang, Erik Vee, Sergei Vassilvitskii, John Tomlin, Jayavel Shanmugasundaram, Tasos Anastasakos and Oliver Kennedy

Abstract: We discuss a multi-objective/goal programming model for the allocation of inventory of graphical advertisements. The model considers two types of campaigns: guaranteed delivery (GD), which are sold months in advance, and non-guaranteed delivery (NGD), which are sold using real-time auctions. We investigate various advertiser and publisher objectives such as (a) revenue from the sale of user visits, clicks and conversions, (b) future revenue from the sale of NGD inventory, and (c) “fairness” of allocation. While the first two objectives are monetary, the third is not. This combination of demand types and objectives leads to potentially many variations of our model, which we delineate and evaluate. Our experimental results, which are based on optimization runs using real data sets, demonstrate the effectiveness and flexibility of the proposed model.

Paper Nr: 88
Title:

GENERALIZED DISAGGREGATION ALGORITHM FOR THE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS AND MULTIPLE ROUTES

Authors:

Rita Macedo, Saïd Hanafi, François Clautiaux, Cláudio Alves and J. M. Valério de Carvalho

Abstract: In this paper, we address the VRP with multiple routes and time windows. For this variant of the VRP, there is a time interval within which every customer must be visited. In addition, every vehicle is allowed to perform more than one route within the same planning period. Here, we propose a general disaggregation algorithm that improves the exact approach described in (Macedo et al., 2011). We describe a novel rounding rule and a new node disaggregation scheme based on different discretization units. We describe a new integer programming model for the problem, which can be used, with a slight modification, to exactly assess whether a given solution is feasible or not. Finally, we report some computational experiments performed on a set of instances from the literature.

Paper Nr: 135
Title:

A MULTI-CRITERIA APPROACH TO LOCAL ENERGY PLANNING - The Case of Barreiro Municipality

Authors:

Ana Rita Neves, João Carlos Lourenço and Vítor Leal

Abstract: Energy planning is at the top priorities of local authorities nowadays. Problems such as the depletion of natural resources, the wellbeing of human population and the security of energy supply have became the main drivers to change the current fossil fuel-based energy paradigm. In order to put into practice energy planning processes at the local level, there is a need to provide support methods and tools to local authorities. In this paper we present a decision support methodology for sustainable local energy planning that combines energy modelling and multi-criteria evaluation techniques. The focus of the paper is on the building process of a multi-criteria evaluation model for the municipality of Barreiro, in Portugal. The municipality case revealed that multi-criteria evaluation is a suitable tool for local energy planning.

Paper Nr: 136
Title:

COMBINATIONS OF OPTION SPREADS

Authors:

Dmytro Matsypura and Vadim G. Timkovsky

Abstract: Having been constructed as trading strategies, option spreads are also used in margin calculations for offsetting positions in options. All option spreads that appear in trading and margining practice have two, three or four legs. It is well-known that the option spreads with three and four legs are combinations of two option spreads with two legs, and that hedging mechanisms of these combinations consolidate hedging mechanisms of their components. Although more complex combinations with similar properties can be traced in regulatory literature of 2003, they have not yet been studied and used. In this paper we develop a theory for the construction of multi-leg option spreads as combinations of well-known option spreads with two, three and four legs. We show how multi-leg option spreads with extreme properties can maximize arbitrage opportunities in trading options and substantially reduce margin requirements for option portfolios.

Short Papers
Paper Nr: 10
Title:

ENGINE CALIBRATION PROCESS OPTIMIZATION

Authors:

Erica Klampfl, Jenny Lee, David Dronzkowski and Kacie Theisen

Abstract: Before an engine can be scheduled in the Product Development cycle for inclusion in a vehicle, it must be calibrated in such a way that it satisfies a variety of regulatory tests over a range of conditions. The current engine calibration process involves conducting a design of experiments at a representative number of steady state points in order to satisfy all required regulatory tests: test engineers use a standard 16×16 grid with standard grid spacing and then conduct a design of experiments on a subset of those points - about 120 of them. This work explores how to reduce the engine calibration process time by finding the best 16×16 grid choice (i.e. the best spacing on both the engine speed and torque axes) and the minimum number of points on the grid to test in order to satisfy regulatory constraints around NOX , particulate matter, noise, and fuel consumption. Our proposed method models the problem as a Binary Integer Program that simultaneously selects the best grid spacing and optimized number of points to test, while guaranteeing that all specified constraints hold. We present an example that demonstrates how we can reduce the number of necessary test points by approximately 56%.

Paper Nr: 16
Title:

INTERVAL AVAILABILITY ANALYSIS OF A TWO-ECHELON, MULTI-ITEM SYSTEM

Authors:

Ahmad Al Hanbali and Mattieu van der Heijden

Abstract: In this paper we analyze the interval availability of a two-echelon, multi-item system. Modeling the system as a Markov chain we analyze the interval availability of the system. We compute in closed and exact form the expectation and, the variance of the availability during a finite time interval [0,T]. We use these characteristics together with the probability that interval availability is equal to one to approximate the survival function using a Beta distribution. Comparison of our approximation with simulation shows excellent accuracy, especially for points that are practically most relevant.

Paper Nr: 29
Title:

DEVELOPMENT OF SEQUENTIAL ASSOCIATION RULES FOR PREVENTING MINOR-STOPPAGES IN SEMI-CONDUCTOR MANUFACTURING

Authors:

Sumika Arima, Ushio Sumita and Jun Yoshii

Abstract: In semi-conductor manufacturing, the machine downtimes due to minor-stoppages often exceed 40% of the working hours of a day, and would amount to the huge loss. However, effective methodological tools for predicting and preventing the minor-stoppages are hard to come by. The purpose of this research is to fill this gap by establishing effective preventive maintenance policies for controlling minor-stoppages. Our approach is to develop association rules based on sequential data along the time axis so that the resulting rules could be used for predicting occurrences of certain minor-stoppages. The proposed methodology is applied to a real data set and yields two preventive maintenance policies in a concrete form, thereby demonstrating its power and usefulness. While the paper focuses on the testing process, the methodology proposed in this paper is valid for other production processes, provided that similar sequential data could be collected.

Paper Nr: 41
Title:

BEAM ANGLE OPTIMIZATION IN IMRT USING PATTERN SEARCH METHODS: INITIAL MESH-SIZE CONSIDERATIONS

Authors:

Humberto Rocha, Joana Matos Dias, Brígida Ferreira and Maria do Carmo Lopes

Abstract: In radiotherapy treatments, the selection of appropriate radiation incidence directions is decisive for the quality of the treatment, both for appropriate tumor coverage and for enhance better organs sparing. However, the beam angle optimization (BAO) problem is still an open problem and, in clinical practice, beam directions continue to be manually selected by the treatment planner in a time-consuming trial and error iterative process. The goal of BAO is to improve the quality of the radiation incidence directions used and, at the same time, release the treatment planner for other tasks. The objective of this paper is to discuss the benefits of using pattern search methods in the optimization of the BAO problem. Pattern search methods are derivative-free optimization methods that require few function value evaluations to progress and converge and have the ability to avoid local entrapment. These two characteristics gathered together make pattern search methods suited to address the BAO problem. Considerations about the initial mesh-size importance and other strategies for a better coverage and exploration of the BAO problem search space will be debated.

Paper Nr: 42
Title:

MULTILEVEL UNIT COMMITMENT IN SMART GRIDS

Authors:

Maurice G. C. Bosman, Albert Molderink, Vincent Bakker, Gerard Smit and Johann L. Hurink

Abstract: This paper focuses on the planning of electricity resources in the developing electricity infrastructure. First we model the existing infrastructure and extend this model to a smart grid infrastructure, where we focus on the large scale introduction of small electricity generators, leading to generation possibilities at both ends of the electricity network. Then the traditional Unit Commitment Problem (UCP) is given. We extend this formulation to the Multilevel Unit Commitment Problem (MUCP), where we describe and include the possibilities that arise in the developing smart grid, in a general way. Based on the characteristics of the problem with its subdivision into different levels, a planning method for the MUCP is described. Finally we solve and analyze a scenario, where a fleet of 5000 houses is added to a small collection of power plants.

Paper Nr: 45
Title:

SHOULD A COMPANY INVEST IN TRAINING - Costs/Benefits of PMP Certification on a Construction Project

Authors:

Malgorzata Plaza, Komal Naz and Anthony Sangra

Abstract: Training is an attractive solution in times where economy experiences a decline in the supply of skilled workers, which is the current trend in the Canadian construction industry. Regardless of its form, employee’s training is expensive, so its benefits should be carefully assessed to assure a proper return from the investment. Research offers several methods, which can be used to measure the outcomes of training. Neither of those methods includes the non-linear changes of performance due to the “learning on the job” effect, which can be depicted by an employee’s progress curve. This paper explores various training assessment approaches and offers analytical decision model. The model can be used to evaluate the impact of employee’s progress curve on the time after which the benefits of training balance its costs. The model is illustrated with a real case of a construction project, in which cost effectiveness of hiring a senior PM is compared to training of a senior and a junior PMs, who are with the company for a number of years. The results of the study demonstrate that training of a senior PM is the most beneficial option.

Paper Nr: 47
Title:

TRANSMISSION EXPANSION PLANNING WITH RE-DESIGN - A Greedy Randomized Adaptive Search Procedure

Authors:

Rosa Figueiredo, Pedro Henrique González Silva and Michael Poss

Abstract: Transmission expansion planning with re-design has been recently proposed in the literature to improve on the classical transmission expansion planning by allowing to cut-off circuits while expanding the network. Although the reductions in the solution costs are significant, the resulting mixed-integer linear programming formulations are very difficult to solve exactly for large networks. In this work, we propose the first metaheuristic for the transmission expansion planing problem with re-design: a simple yet efficient GRASP metaheuristic. We show on realistic networks for which the optimal solutions are known that our method is able to provide in short amounts of time feasible solutions as cheap as the optimal ones. Moreover, we are able to compute a new feasible solution for benchmark instance Brazil Southeast that is cheaper than the best solution from the literature.

Paper Nr: 69
Title:

SEMIDEFINITE RELAXATIONS FOR THE SCHEDULING NUCLEAR OUTAGES PROBLEM

Authors:

Abdel Lisser, Agnes Gorge and Riadh Zorgati

Abstract: We investigate semidefinite relaxations for solving aMIQP (Mixed-Integer Quadratic Program) formulation of the scheduling of nuclear power plants outages, which is extremely hard to solve with CPLEX. Based on our numerical experiments, results obtained with semidefinite relaxations improve those obtained with continuous relaxation: the gap between the optimal solution and the continuous relaxation is on average equal to 1.80% whereas the semidefinite relaxation yields an average gap of 1.56\%. These bounds are then used to obtain a feasible solution with a randomized rounding procedure.

Paper Nr: 81
Title:

A MULTI-CRITERIA SORTING APPROACH FOR DIAGNOSING MENTAL DISABILITIES

Authors:

Paulo Freitas, Carlos Henggeler Antunes and Jorge Dias

Abstract: A multi-criteria model tackled by an outranking method devoted to the sorting problem is presented to support decision making in assessing individual mental disabilities using information required in the Clinical Dementia Rating scale. This diagnosis process is a critical factor for adapting treatments to the current stage of the disease and improving health care and quality of life. The criteria required in the Clinical Dementia Rating scale have been considered as an input for developing our multi-criteria model, the output of which is the classification of each individual under evaluation in a pre-defined ordered class (category) as an indicator of the revealed level of mental disabilities. A method based on the exploitation of an outranking relation for the sorting problem is used to compare the individual information according to multiple evaluation criteria with reference profiles (specified standards) that define the boundaries of the classes. This methodological approach is substantially different from the ones based on the aggregation of the different criteria using weighted-sums to produce a “common value” measure. The method requires meaningful technical parameters, such as weights (herein perceived as true importance coefficients of the multiple evaluation aspects), distinct thresholds to ascertain the outranking classification, and a cutting level establishing the exigency of the classification. A realistic example using the decision support system Iris is presented to illustrate the results.

Paper Nr: 85
Title:

EMODS: A NOVEL EVOLUTIONARY METAHEURISTIC BASED IN THE AUTOMATA THEORY FOR THE MULTIOBJECTIVE OPTIMIZATION OF COMBINATORIALS PROBLEMS

Authors:

Elias David Nino Ruiz and Anangelica Isabel Chinchilla Camargo

Abstract: This paper states a novel Evolutionary Metaheuristic based in the Automata Theory for the Multiobjective Optimization of Combinatorial Problems named EMODS. The proposed algorithm uses the natural selection theory to explore the feasible solutions space of a Combinatorial Problem. Due to this, local optimums are avoided. Also, EMODS takes advantage in the optimization process from the Metaheuristic of Deterministic Swapping to avoid finding unfeasible solutions. The proposed algorithm was tested using well known instances from the TSPLIB with three objectives. Its results were compared against four Multiobjective Simulated Annealing inspired Algorithms using metrics from the specialized literature. In every case, the EMODS results on the metrics were always better and in some of those cases, the distance from the Real Solutions was 4%.

Paper Nr: 95
Title:

A PARALLEL HEURISTIC FOR FAST TRAIN DISPATCHING DURING RAILWAY TRAFFIC DISTURBANCES: EARLY RESULTS

Authors:

Syed Muhammad Zeeshan Iqbal, Håkan Grahn and Johanna Törnquist Krasemann

Abstract: Railways are an important part of the infrastructure in most countries. As the railway networks become more and more saturated, even small traffic disturbances can propagate and have severe consequences. Therefore, efficient re-scheduling support for the traffic managers is needed. In this paper, the train real-time re-scheduling problem is studied in order to minimize the total delay, subject to a set of safety and operational constraints. We propose a parallel greedy algorithm based on a depth-first branch-and-bound search strategy. A number of comprehensive numerical experiments are conducted to compare the parallel implementation to the sequential implementation of the same algorithm in terms of the quality of the solution and the number of nodes evaluated. The comparison is based on 20 disturbance scenarios from three different types of disturbances. Our results show that the parallel algorithm; (i) efficiently covers a larger portion of the search space by exchanging information about improvements, and (ii) finds better solutions for more complicated disturbances such as infrastructure problems. Our results show that the parallel implementation significantly improves the solution for 5 out of 20 disturbance scenarios, as compared to the sequential algorithm.

Paper Nr: 98
Title:

PLANNING BUS DRIVER ROSTERS

Authors:

Marta Mesquita, Margarida Moz, Ana Paias and Margarida Pato

Abstract: This paper proposes a methodology for planning bus driver rosters with days off patterns in public transit companies. The problem is modeled as a mixed integer linear programming problem which is solved with special devised branch-and-bound techniques by a standard MILP solver. The new methodology was tested on instances of two companies operating in Portugal. Two types of days off rules giving rise to rosters with specific days off patterns are compared. The computational experiment shows promising results which suggest that the proposed framework can be used as a tool to evaluate and discuss different days off patterns within public transit companies.

Paper Nr: 104
Title:

TOURISM-KM - A Variant of MMKP Applied to the Tourism Domain

Authors:

Romain Picot-Clémente, Florence Mendes, Christophe Cruz and Christophe Nicolle

Abstract: We are interested in an original real-world problem coming from tourism field. We describe a modelling of the problem and propose a first approach that mixes knowledge management and operational research methods. Our algorithms have been implemented in order to produce tourism solutions that are not unique for a given request but that take into account the preferences of the tourist user and provide a personalized solution. We report computational results obtained on real-world instances.

Paper Nr: 105
Title:

MULTICRITERIA SELECTION OF AN AIRCRAFT WITH NAIADE

Authors:

João Carlos C. B. Soares de Mello, João Erick M. Fernandes and Luiz Flávio Autran M. Gomes

Abstract: This article deals with the problem of multicriteria selection of an aircraft. The problem has eight alternatives to be evaluated under eleven different criteria, whose measurements can be exact, stochastic, or fuzzy. The technique chosen for analyzing and then finding a solution to the problem is the multicriteria decision aiding method named NAIADE (Novel Approach to Imprecise Assessment and Decision Environments). The method used allows tackling the problems by working with quantitative as well as qualitative criteria under uncertainty and imprecision. Another considerable advantage of NAIADE over other multicriteria methods relies in its characteristics of not requiring a prior definition of the weights by the decision maker. As a conclusion it can be said that the use of NAIADE provided for consistent results to that aircraft selection problem.

Paper Nr: 106
Title:

FLOW-BASED PROGRAMMING AS A SOLUTION FOR CLOUD COMPUTING REQUIREMENTS

Authors:

Marcel R. Barros, Charles C. Miers, Marcos Simplício, Tereza C. M. B. Carvalho, Jan-Erik Mångs, Bob Melander and Victor Souza

Abstract: Cloud computing services provide a new way of deploying applications over the Internet, as well a prominent approach for achieving enhanced scalability. Usually, exploration of cloud computing resources relies on a regular programming paradigm (such as Oriented Object Programming), depending on adjustments to deal with details inherent to the cloud provider and the issues related to scalability of regular programming paradigm. This paper addresses how Flow-Based Programming (FBP), a software architecture model based on Functional Programming, can be used as a solution to the challenges involving the achievement of distributed systems requirements. Firstly, we present a review of the concepts of FBP. We analyze Live Distributed Objects, Microsoft Orleans, and Yahoo! S4 under FBP perspective, providing a comparison among these solutions based on FBP criteria. Finally, we present an analysis of how FBP could be used to provide a better way to developers create scalable applications such as cloud computing.

Paper Nr: 115
Title:

WIRELESS MESH NETWORKS PLANNING BASED ON PARAMETERS OF QUALITY OF SERVICE

Authors:

Marlon da Silva, Edson Luiz França Senne and Nandamudi Lankalapalli Vijaykumar

Abstract: The use of QoS parameters to evaluate the quality of service in a mesh network is essential mainly when providing multimedia services. This paper proposes an algorithm for planning wireless mesh networks in order to satisfy some QoS parameters, given a set of test points (TPs) and potential access points (APs). Examples of QoS parameters include: probability of packet loss and mean delay in responding to a request. The proposed algorithm uses a Mathematical Programming model to determine an adequate topology for the network and Monte Carlo simulation to verify whether the QoS parameters are being satisfied. The results obtained show that the proposed algorithm is able to find satisfactory solutions.

Paper Nr: 120
Title:

DYNAMIC RESPONSE ANALYSIS OF MULTIBODY SYSTEM IN DISCRETE EVENT SIMULATION

Authors:

Namkug Ku, Sol Ha, Myung-Il Roh and Kyu-Yeul Lee

Abstract: There are several kinds of mechanical systems that are under event-triggered conditions. For the dynamic analysis of such mechanical systems, a simulation program that can generate equations of motion for mutibody systems in the discrete-event simulation framework was developed. For complex multibody systems, a dynamics kernel was developed to generate the equations of motion for multibody systems based on multibody dynamics. To generate the equations of motion, the recursive formulation method was used. Using the developed dynamics kernel, the dynamic responses of multibody systems can be carried out under continuous conditions. The general multibody dynamics kernel, however, cannot deal with discontinuous-state variables and event-triggered conditions. The multibody dynamics kernel, therefore, was integrated into the discrete-event simulation program to deal with multibody systems in discontinuous environments. The discrete-event simulation program was developed based on the discrete-event system specification (DEVS) formalism, which is a modular and hierarchical formalism for analyzing systems under event-triggered conditions.

Paper Nr: 126
Title:

A GENETIC ALGORITHM FOR CROP ROTATION

Authors:

Angelo Aliano Filho, Helenice de Oliveira Florentino and Margarida Vaz Pato

Abstract: In the last few years, crop rotation has gained attention due to its economic, environmental and social importance which explains why it can be highly beneficial for farmers. This paper presents a mathematical model for the Crop Rotation Problem (CRP) that was adapted from literature for this highly complex combinatorial problem. The CRP is devised to find a vegetable planting program that takes into account green fertilization restrictions, the set-aside period, planting restrictions for neighboring lots and for crop sequencing, demand constraints, while, at the same time, maximizing the profitability of the planted area. The main aim of this study is to develop a genetic algorithm and test it in a real context. The genetic algorithm involves a constructive heuristic to build the initial population and the operators of crossover, mutation, migration and elitism. The computational experiment was performed for a medium dimension real planting area with 16 lots, considering 29 crops of 10 different botanical families and a two-year planting rotation. Results showed that the algorithm determined feasible solutions in a reasonable computational time, thus proving its efficacy for dealing with this practical application.

Paper Nr: 137
Title:

GENETIC ALGORITHM FOR SOLVING A MULTI-OBJECTIVE HELICOPTER ROUTING PROBLEM

Authors:

Fubin Qian

Abstract: The petroleum industry uses helicopters to transport employees to and from the offshore installations. The helicopter transportation represents a major risk for the employees. The helicopter routing problem is an application of vehicle routing problem with combined pickup and delivery demands, which usually minimizes the total cost of the routes and the fleet size (the number of routes) in a classical form. It is also of interest to minimize the transportation risk. In this paper, a multi-objective genetic algorithm is presented for the helicopter routing problem. The algorithm uses a variation of the cluster-first route-second method for routing helicopters. We apply the proposed algorithm to instances derived from real data and evaluate its effectiveness by comparing with e-constraint approach with a state-of-the-art single-objective tabu search metaheuristic.

Paper Nr: 147
Title:

A KNAPSACK PROBLEM APPROACH FOR OPTIMAL ALLOCATION OF MAINTENANCE RESOURCES ON ELECTRIC POWER DISTRIBUTION NETWORKS

Authors:

Eduardo Tadeu Bacalhau, Fábio Luiz Usberti, Christiano Lyra Filho and Celso Cavellucci

Abstract: The definitions of optimal preventive and corrective maintenance of electric power distribution networks can be seen as a special case of a knapsack problem. This paper proposes a dynamic programming approach to deal with this problem. The approach is developed for one or more years of planning horizon. Case studies compare the optimal dynamic programming approach with an heuristic method.

Posters
Paper Nr: 68
Title:

OPTIMIZING OPERATIONS OF LARGE WATER SUPPLY NETWORKS - A Case Study

Authors:

Derek Verleye, El-Houssaine Aghezzaf and Dimi Defillet

Abstract: In this paper we propose a mathematical programming model for a large drinking water supply network and discuss some possible extensions. The proposed optimization model is of a real water distribution network, the largest water supply network in Flanders. The problem is nonlinear, nonconvex and involves some binary variables, making it belong to the class of NP-hard problems. We discuss a way to convexify the nonconvex term and show some results on two case instances of the actual network.

Paper Nr: 75
Title:

EFFICIENCY EVALUATION IN ACADEMIC UNITS APPLYING DATA ENVELOPMENT ANALYSIS - Initial State of Project

Authors:

Horacio Rojo, Silvia Adriana Ramos, Pedro Tolón Estarelles, Claus Stegmann, Leandro J. Raspa and Diego Castro

Abstract: The aim of this paper is to present a procedure to look into the relative efficiency of university departments in order to make a good allocation of resources. This procedure uses a model based on Data Envelopment Analysis (DEA). DEA measures relative efficiency of a set of alternatives (decision making units – DMUs) that consume multiple inputs and produce multiple outputs. Results of the model will help to plan development of university departments in Facultad de Ingeniería of Universidad de Buenos Aires.

Paper Nr: 101
Title:

A HIERARCHICAL APPROACH BASED ON LINEAR AND STOCHASTIC PROGRAMMING FOR THE EMPTY CONTAINER ALLOCATION PROBLEM

Authors:

Jorge Luis Morales B. and Ciro Alberto Amaya G.

Abstract: This paper proposes a solution method to the problem of allocating an empty container fleet to a set of stocking yards in order to minimize empty container stock and repositioning costs under uncertainties in demand, supply, container damages and repairing times. We propose an approximate solution for the problem based on a hierarchical approach. We used random data from different probability functions to generate problem instances and evaluate robustness and performance. We find that the proposed model solves the single location inventory problem in a very short time while obtaining high robustness and each one can be solved independently. This approach allows liners to reduce the complexity of an aggregate stochastic problem by solving multiple independent stochastic inventory problems. Additionally to other similar works, the presented models consider random container damages and repairing times.

Paper Nr: 129
Title:

EXPERIENTIAL STATE AND EFFECT OF FACTORS ON THE DIMENSIONS OF OFFER IN A SERVICE COMPANY - Using Confirmatory Factor Analysis: A Five Factor Model

Authors:

Erick Guerrero Camacho and Richard Huamán Ramirez

Abstract: In recent years, experience is one of the major topics regarding the business world, which involves even more the research in management and engineering. Customer experience is conceptualized in management as the unforgettable event where the customer, the product and/or service, and the environment interact, and where customers respond in a sensorial, affective, intellectual, behavioral and social fashion to stimuli provoked by companies or brands. Experience Engineering identifies these stimuli as clues about experience and centralizes on the proposal of humanistic y mechanical contexts, having as sources: the product, the service, and the environment. Among the research it is possible to identify, through a scientific study using Confirmatory Factor Analysis, the experiential state of the San Antonio Bakery, and the effect of generated factors on the dimensions of an experientially conceptualized offer. It is found that humanistic contexts influence considerably on affective, intellectual and behavioral experiences of customers, and that mechanical contexts influences considerably on sensorial and affective experiences.

Paper Nr: 139
Title:

MARGINING COMPONENT OF THE STOCK MARKET CRASH OF OCTOBER 2008 - A Lesson of the Struggle with Combinatorial Complexity

Authors:

Dmytro Matsypura and Vadim G. Timkovsky

Abstract: In July 2005 the US stock market started using the risk-based approach to margining customer accounts gradually excluding from margining practice the strategy-based approach, which has been used for more than four decades. In this paper we argue that this change has a direct link to the stock market crash of October 2008. We also show that among the main reasons of this change are high strategy-based margin requirements in comparison with much lower risk-based, the combinatorial complexity of the strategy-based approach, and the failure of the brokerage industry to adopt the achievements of combinatorial optimization.

Paper Nr: 144
Title:

INTRODUCTION TO MULTICRITERIA TECHNIQUES

Authors:

Jorge Azevedo Santos and Elsa Rosário Negas

Abstract: The systematic analysis and decision making in companies, particularly in an environment of risk, are now a major challenge, namely the complexity of each problem. Multicriteria techniques are applied a long time ago and had an important development and expanded its application areas. The simple decisions, which are considered routine, given the frequency they repeat themselves tend now to be reviewed and reanalyzed in order to be efficient. Sort a decision as efficient as we rank a decision when compared with other decisions in which the chosen factors have worse performance, or deciding factors, for example, the ratio between consumption and production is less attractive.