ICORES 2018 Abstracts


Area 1 - Methodologies and Technologies

Full Papers
Paper Nr: 4
Title:

The Effect of Marketing Imperfection Variables on Production in the Context of Brazilian Agriculture

Authors:

Geraldo da Silva e Souza and Eliane Gonçalves Gomes

Abstract: In the context of the Brazilian agriculture it is of importance for policy makers the assessment of the effect on production of variables related to market imperfections. Market imperfection or asymmetry occurs when farmers are subjected to different market conditions depending on their size or their importance on overall state production. Relatively large rich farmers obtain lower input prices and may sell their production at lower prices making competition harder for small farmers. Market imperfections are typically associated with infrastructure, environment control requirements and the presence of technical assistance. In this article, at county level and using agricultural census data, we estimate the elasticities of these variables on production by maximum likelihood methods. We show that all these variables affect production significantly. Technological inputs dominate the production response, followed by labor and land. Environment control has a positive effect on production, as well as technical assistance. The logistics of production mostly affects technical efficiency. The proportion of forested areas has a negative elasticity. We also test technical assistance for endogeneity.

Paper Nr: 7
Title:

Dynamic Pricing Strategies in a Finite Horizon Duopoly with Partial Information

Authors:

Rainer Schlosser and Keven Richly

Abstract: In many applications the sale of perishable products is characterized by competitive settings and incomplete information. While prices of sellers are typically observable, the inventory levels of firms are mutually not observable. In this paper, we analyze stochastic dynamic pricing models in a finite horizon duopoly with partial information. We use a Hidden Markov Model approach to compute strategies that are applicable when the competitor’s inventory level is not observable. Our approach utilizes feedback pricing strategies that are optimal if the competitor’s inventory level is observable. We show that price reactions are balancing two effects: (i) to slightly undercut the competitor’s price to sell more items, and (ii) to use high prices to promote a competitor’s run-out and to act as a monopolist for the rest of the time horizon. Moreover, we compute heuristic strategies that can be applied when the number of competitors is large and their strategies are unknown. We find that expected profits are hardly affected by different information structures as long as the firms’ information is symmetric.

Paper Nr: 8
Title:

A Heuristic for a Rich and Real Two-dimensional Woodboard Cutting Problem

Authors:

Claudio Arbib, Fabrizio Marinelli, Andrea Pizzuti and Roberto Rosetti

Abstract: Cutting operations in manufacturing are characterized by practical requirements and utility criteria that usually increase the complexity of formulations or, even worse, are difficult to be modeled in terms of mathematical programming. However, disregarding or just simplifying those requirements often leads to solutions considered not attractive or even useless by the manufacturer. In this paper we consider a rich two-dimensional cutting stock problem that covers the whole specification of a family of wood cutting machines produced by a worldwide leader in industrial machinery manufacturing. A sequential value correction heuristic is implemented to minimize the employed stock area while reducing additional objective functions.

Paper Nr: 10
Title:

Impacts Analysis towards a Sustainable Urban Public Transport System

Authors:

Darwin Aldas, John Reyes, Luis Morales, Pilar Pazmiño, José Núñez and Bladimir Toaza

Abstract: Nowadays, both big and small cities look to optimize their urban public transport systems through models that allow reduction of transfer time and environmental impacts, to create sustainable cities. Thus, cities of Latin American countries are adapting their public transport systems to energetic sustainability conditions. This study analyzes the impacts of transport models and chooses the best alternative, considering four cities with a high urban mobility index and optimal conditions of sustainable development. A review of scientific literature is conducted and priority criteria, such as traffic, environmental impact, social impact, and economic impact are established and evaluated via the Analytical Hierarchy Process (AHP) decision making method. As a result, the AHP model defines the city of Curitiba as the best sustainable transport alternative, with 31, 8% against 27, 6% of Singapore, 17, 8% of Santiago de Chile and Montreal with 22, 9%. The proposal uses a four-step transport model: trip generation, trip distribution, mode choice and route assignment.

Paper Nr: 17
Title:

Integrating Fuzzy Cognitive Mapping and Bayesian Network Learning for Supply Chain Causal Modeling

Authors:

Behnam Azhdari

Abstract: In this study, by integrating fuzzy cognitive mapping (FCM) and causal Bayesian network (CBN) learning, a model of causal links among supply chain enablers, supply chain management practices and supply chain performances is developed. For FCM development, fuzzy causal knowledge of a panel of experts in SCM is elicited. Also, an industry survey data used in a Bayesian learning process to create a CBN. By applying analytical modifications, the resultant CBN model is modified to reach better fit indices, suggesting a new approach in Bayesian learning. Integrating FCM and CBN models, resulted in more valid causal relations that are based on these two different methodologies. The findings of this study support the notion that SC enablers, especially IT technologies, don't have direct impact on SC performance. Also it is revealed that in any tier of supply chain concepts; there may be some important intra-relations which worth further studies.

Paper Nr: 22
Title:

Packing Circles and Irregular Polygons using Separation Lines

Authors:

Jeinny Peralta, Marina Andretta and José Fernando Oliveira

Abstract: In this paper we propose a nonlinear mathematical model for the problem of packing circles, convex and non-convex irregular polygons, within a rectangular envelope to be produced, obeying containment constraints and non-overlapping constraints; the objective of the problem is to minimize the area of the rectangular envelope. We consider free rotations of the polygons and use separation lines to ensure non-overlapping. Computational tests were run using instances presented in the literature that deal with circles and polygons simultaneously; different solutions, in which the area of the rectangular envelope is smaller than or equal to the ones found in the literature were found in most cases, and the execution time is very low. This indicates that our model is computationally efficient.

Paper Nr: 23
Title:

Box Constrained Low-rank Matrix Approximation with Missing Values

Authors:

Manami Tatsukawa and Mirai Tanaka

Abstract: In this paper, we propose a new low-rank matrix approximation model for completing a matrix with missing values. Our proposed model contains a box constraint that arises from the context of collaborative filtering. Although it is unfortunately NP-hard to solve our model with high accuracy, we can construct a practical algorithm to obtain a stationary point. Our proposed algorithm is based on alternating minimization and converges to a stationary point under a mild assumption.

Paper Nr: 34
Title:

Fiber Cable Network Design with Operations Administration & Maintenance Constraints

Authors:

Vincent Angilella, Matthieu Chardy and Walid Ben-Ameur

Abstract: We introduce two specific design problems of optical fiber cable networks that differ by a practical maintenance constraint. An integer programming based method including valid inequalities is introduced for the unconstrained problem. We propose two exact solution methods to tackle the constrained problem: the first one is based on mixed integer programming including valid inequalities while the second one is built on dynamic programming. The theoretical complexities of both problems in several cases are proven and compared. Numerical results assess the efficiency of both methods in different contexts including real-life instances, and evaluate the effect of the maintenance constraint on the solution quality.

Paper Nr: 43
Title:

Behaviour of a Hybrid ILS Heuristic on the Capacitated Profitable Tour Problem

Authors:

Hayet Chentli, Rachid Ouafi and Wahiba Ramdane Cherif-Khettaf

Abstract: In the present paper, we study the behaviour of a hybrid Iterative Local Search heuristic (ILS). A Large Neighborhood Search heuristic (LNS) and a Variable Neighborhood Descent with Random neighborhood ordering (RVND) are used in the local search phase of the proposed ILS. The approach is evaluated on a well-known variant of the Vehicle Routing Problem (VRP) called Capacitated Profitable Tour Problem (CPTP). In this variant, the vehicles are no longer required to visit all the customers. However, a specific profit is obtained each time a customer is visited. The goal of the CPTP is to design routes with maximum difference between collected profits and routing costs, which satisfy the capacity constraint of the vehicles. The experimental study consists in comparing different combinations of ILS, LNS and RVND. The computational results show that the hybridization of the three heuristics leads to better solutions. Furthermore, comparisons with a Variable Neighborhood Search and two Tabu Searches from the literature indicates that our hybrid approach is competitive.

Paper Nr: 65
Title:

Using Goal Programming on Estimated Pareto Fronts to Solve Multiobjective Problems

Authors:

Rodrigo Lankaites Pinheiro, Dario Landa-Silva, Wasakorn Laesanklang and Ademir Aparecido Constantino

Abstract: Modern multiobjective algorithms can be computationally inefficient in producing good approximation sets for highly constrained many-objective problems. Such problems are common in real-world applications where decision-makers need to assess multiple conflicting objectives. Also, different instances of real-world problems often share similar fitness landscapes because key parts of the data are the same across these instances. We we propose a novel methodology that consists of solving one instance of a given problem scenario using computationally expensive multiobjective algorithms to obtain a good approximation set and then using Goal Programming with efficient single-objective algorithms to solve other instances of the same problem scenario. We propose three goal-based objective functions and show that on a real-world home healthcare planning problem the methodology can produce improved results in a shorter computation time.

Paper Nr: 68
Title:

Capacitated Arc Routing Problem over Sparse Underlying Graph under Travel Costs Uncertainty

Authors:

Sara Tfaili, Abdelkader Sbihi, Adnan Yassine and Ibrahima Diarrassouba

Abstract: In this paper, we study the capacitated arc routing problem over sparse underlying graphs under travel costs uncertainty. In particular, we work with Multiple-Scenario Min-Max CARP over sparse underlying graphs. We present a mathematical formulation of the problem. A greedy heuristic algorithm and an adapted tabu-search algorithm are developed to solve the problem. The computational experiments show the effectiveness of these two algorithms for different sizes of instances as well for different number of scenarios.

Short Papers
Paper Nr: 11
Title:

Mathematical Programs and Computations for a Class of Anti-aircraft Mission Planning Problems

Authors:

Trang T. Nguyen, Trung Q. Bui, Bang Q. Nguyen and Su T. Le

Abstract: The theater defense distribution is an important problem in the military that determines strategies against a sequence of offensive attacks in order to protect his targets. This study focuses on developing mathematical models for three important defense problems that generate anti-aircraft mission plans for a group of missile battalions. The simple Anti-aircraft Launching Assignment problem specifies number of missiles should be launched from each battalion to each fleet of attacking aircraft to maximize the defensive effectiveness, provided that the locations of missile battalions are given. On the other hand, the Anti-aircraft Mission Planning problem maximizes the defender’s effectiveness using all his available battalions, while the Inverse Antiaircraft Mission Planning problem computes necessary weapon resources (battalions and their missiles) to obtain a given defensive effectiveness value. The proposed formulations are Integer Programs and proved as NP-hard. A comprehensive set of experiments is then evaluated to show that these proposed programs can be applied to solve fast real-life instances to optimality.

Paper Nr: 14
Title:

A Data Quality Dashboard for CMMS Data

Authors:

Ralf Gitzel, Subanatarajan Subbiah and Christopher Ganz

Abstract: Reliability or survival data analysis is an important tool to estimate the life expectancy and failure behaviour of industrial assets such as motors or pumps. One common data source is the Computerized Maintenance Management System (CMMS) where all equipment failures are reported. However, the CMMS typically suffers from a series of data quality problems which can distort the calculation results if not properly addressed. In this paper, we describe the possible data quality problems in reliability data with a focus on CMMS data. This list of problems is based on the results of six case studies conducted at our company. The paper lists a set of metrics which can be used to judge the severity. We also show how the impact of data quality issues can be estimated. Based on this estimate, we can calibrate a series of metrics for detecting the problems shown.

Paper Nr: 20
Title:

Diffusion and Disappearance of Traffic Congestion under Steady State in a Graph Network

Authors:

Masaru Kaji

Abstract: Traffic jams on highways or crowds of people in stations during rush hours are social phenomena that have attracted the attention of many scientists. It is known that the stop-and-go wave is a cluster wave that propagates in a direction opposite to the movement of vehicles or pedestrians. A city consists of many roads and intersections in the form of a network, and the stop-and-go wave will propagate according to the road network. Therefore, observations need to be made from a broader perspective to analyze the interconnections between roads when considering traffic congestion. In this study, we use a graph-based control method and define a graph-shaped traffic network considering the characteristics of traffic flow. We set the steady state as the initial condition in the network and create a traffic jam on a certain road intentionally. Following the congestion, we show the manner in which the traffic congestion wave spreads, and discuss the mechanism in which it propagates from one road to a connecting road. This also shows the kind of situations in which traffic jams propagate and diminish; the simulation results correspond to the theoretical value integrated quantitatively. This will be helpful in solving the traffic congestion problem.

Paper Nr: 26
Title:

Eco-Gresilient: Coalescing Ingredient of Economic, Green and Resilience in Supply Chain Network Design

Authors:

Ahmed Mohammed, Irina Harris and Reda Nujoom

Abstract: This research presents a new approach that considers green and resilience dimensions in addition to economic (eco-gresilient, henceforth) aspects to design an eco-gresilient supply chain network. Thus, fuzzy AHP (analytical hierarchy process) is used to determine the relative weight of evaluation criteria for each resilience pillars (robustness, agility, leanness and flexibility (RALF)), and then it is used for assigning the importance weight for each potential facility with respect to RALF. The determined weights revealed via fuzzy AHP are then integrated into a multi-objective optimization model to identify the number of facilities that should be established in the meat supply chain. Three objective functions were formulated and include minimization of total cost and environmental impact and maximization of value of resilience (V-RALF). The ε-constraint approach is used to obtain a set of Pareto solutions. The effectiveness of the developed eco-gresilient multi-objective model is presented on a case study in the meat sector.

Paper Nr: 31
Title:

Optimizing Storage Capacity of Retailers in Stochastic Periodic Inventory Routing Problem

Authors:

Ehsan Yadollahi, El-Houssaine Aghezzaf, Joris Walraevens and Birger Raa

Abstract: A challenging question in Stochastic Periodic Inventory Routing Problem (SPIRP) is how to deal with stochastic demand rates, while minimizing the costs (transportation, inventory, and storage) and finding the best routing system. In this paper, we reformulate the SPIRP model to a safety stock-based SPIRP where the inventory storage capacity at the retailers are considered as variables and retailer’s demand rate is stochastic. The supply chain planner needs to find the best routing system to replenish the retailers with the most optimum level of inventory, while the service level is satisfied in a long term planning horizon. Four different policies for storage capacity optimization are presented, evaluated, and compared in an illustrative example. The impact of storage capacity limitation is considered based on the defined policies to measure their compatibility for different situations.

Paper Nr: 38
Title:

Reducing Disruptive Effects of Service Interruptions in Appointment Scheduling

Authors:

Matthias Deceuninck, Stijn De Vuyst and Dieter Fiems

Abstract: This paper considers appointment scheduling for outpatient services when the service of scheduled patients can be interrupted by emergency arrivals. We consider a single doctor who consults K patients during a fixed-length session. Each patient has been given an appointment time during the session in advance. Our evaluation approach aims at obtaining accurate predictions at a very low computational cost for the waiting times of the patients and the idle time of the doctor. To this end, we investigate a modified Lindley recursion in a discrete-time framework. We assume general, possibly distinct, distributions for the patient's consultation times and allow for individual no-show probabilities. This fast evaluation method is then used in a local search algorithm to provide insights into scheduling with service interruptions. Numerical examples show that this method outperforms simulation optimization and naive approaches in terms of cost and running time.

Paper Nr: 44
Title:

Constructive Heuristics for Periodic Electric Vehicle Routing Problem

Authors:

Tayeb Oulad Kouider, Wahiba Ramdane Cherif-Khettaf and Ammar Oulamara

Abstract: This paper introduces a new variant of the electric vehicle routing problem, named PEVRP for Periodic Electric Vehicles Routing Problem, in which the routing and charging are planned over a multi-period horizon, subject to frequency constraints, limited fleet of electric vehicles available at the depot, intermediate facilities for charging during the trips, and partial charging. The objective of the PEVRP is to minimize the total cost of routing and charging over the time horizon, such that each vehicle could be charged nightly at the deport, and during the day at charging stations if refuelling is necessary. We propose two constructive heuristics. The first one is based on clustering technique that aims at allocating customers per vehicle and per period, and then constructs tour for each vehicle visiting customers and charging stations for refuelling. The second one is based on best insertion strategy, in which each customer is allocated to its best position that minimizes charging and routing cost. Using several parameters setting, we compared and analysed the results of the two proposed approaches on 50 new instances derived from EVRP instances of the literature.

Paper Nr: 46
Title:

A Pooling Strategy for Flexible Repair Shop Designs

Authors:

Hasan Huseyin Turan, Shaligram Pokharel, Andrei Sleptchenko, Tarek Y Elmekkawy and Maryam Al-Khatib

Abstract: We discuss the design problem of a repair shop in a single echelon repairable multi-item spare parts supply system. The repair shop consists of several parallel multi-skilled servers, and storage facilities for the repaired items. The effectiveness of repair shops and the total cost of a spare part supply system depend highly on the design of repair facility and the management of inventory levels of the spare parts. In this paper, we concentrate on a design scheme known as pooling. A repair shop can be considered as a pooled structure if the spare parts can be divided into clusters such that each part type is unambiguously assigned to a single cluster (cell). Nonetheless, it is both an important and tough combinatorial optimization question to determine which type of spares to pool together. We propose a sequential solution heuristic to find the best pooled design by considering inventory allocation and capacity level designation of the repair shop. The numerical experiments show that the suggested solution approach has a reasonable algorithm run time and yields considerable cost reductions.

Paper Nr: 51
Title:

Multi-server Marginal Allocation - With CVaR and Abandonment based QoS Measures

Authors:

Per Enqvist and Göran Svensson

Abstract: Two multi-objective minimization problems are posed, one for Erlang-C queues and one for Erlang-A queues. The objectives are to minimize the cost of added agents while also trying to optimize a quality of service measure. For the Erlang-C system we propose using the Conditional Value-at-Risk measure with waiting time as the loss function. We prove that this quality of service measure is integer convex in the number of servers. For the Erlang-A system we use the fraction of abandoning customers and some rate based weighting function as the service measure. Finally, a numerical comparison of the two system types is performed. The numerical results show the similarities between the two systems in terms of optimal points.

Paper Nr: 53
Title:

Solving the Flight Radius Problem

Authors:

Assia Kamal Idrissi, Arnaud Malapert and Rémi Jolin

Abstract: In this article, we present the flight radius problem on the condensed flight network. The problem is derived from a decision tool for airline managers to analyze and simulate a new market. It concerns the network design and visualization when allocating a new flight. The flight radius problem consists in finding routes passing through a specific flight that represent business opportunities regarding time and cost criteria. It is formulated as finding a maximal subgraph of nodes belonging to routes accepted by a regret function. The regret is defined as a function of the optimal values of the time and cost criteria. In practice, the condensed flight network is stored in a graph database Neo4j. First, we propose a query based on available procedures in the database. Second, we propose a method that uses the regret function to speed up the successive calls to Dijkstra algorithm. Results on a set of real-world instances with different flights (Hub & Spoke) and regret function parameters demonstrate that the algorithm is more efficient than the query and meets real-world response time constraints.

Posters
Paper Nr: 19
Title:

Military Manpower Planning - Towards Simultaneous Optimization of Statutory and Competence Logics using Population based Approaches

Authors:

Oussama Mazari Abdessameud, Filip Van Utterbeeck, Johan Van Kerckhoven and Marie-Anne Guerry

Abstract: Military manpower planning aims to match the required and available staff. Statutory and competence logics are two linked aspects of the military manpower management. Military manpower management involves the long term planning with strategic goals, and also the short term human resources management with operational goals. These two aspects are interdependent; therefore this article proposes a technique to combine both logics in the same integrated model. A combined model allows the simultaneous optimization for both logics. In this article we illustrate a model based on flow network. We present integer programming and goal programming to find optimal solutions.

Paper Nr: 25
Title:

A Two-stage Stochastic Programming Model for the Resource Constrained Project Scheduling Problem under Uncertainty

Authors:

Maria Elena Bruni, Luigi Di Puglia Pugliese, Patrizia Beraldi and Francesca Guerriero

Abstract: Due to the increasing competitiveness of businesses, project planning and scheduling have become a challenging theme in the last years. In this paper, we propose a two-stage stochastic programming model for the resource constrained project scheduling problem, taking into account the stochasticity of activity durations. In this formulation, assuming that some activity duration scenarios are known, resource allocations are taken in the first stage, while scheduling decisions are postponed in the second stage. The resulting problem is a mixed integer problem with recourse, where binary variables appear in the first stage. In order to efficiently solve the problem, a decomposition algorithm is developed, based on the well-known integer L-shaped method. Detailed computational results are presented for a set of benchmark instances taken from the literature.

Paper Nr: 40
Title:

Upper Bounds for the Total Chromatic Number of Join Graphs and Cobipartite Graphs

Authors:

Leandro M. Zatesko, Renato Carmo and André L. P. Guedes

Abstract: We concern ourselves with the combinatorial optimisation problem of determining a minimum total colouring of a graph G for the case wherein G is a join graph G = G_1 ∗ G_2 or a cobipartite graph G = (V_1 ∪ V_2, E(G)). We present algorithms for computing a feasible, not necessarily optimal, solution for this problem, providing the following upper bounds for the total chromatic numbers of these graphs (let n_i := |V_i| and _i := (G_i) for i ∈ {1, 2} and  ∈ {∆, χ, χ′, χ′′}): χ′′(G) ≤ max{n_1, n_2} + 1 + P(G_1, G_2) if G is a join graph, wherein P(G_1, G_2) := min{∆_1 + ∆_2 + 1, max{χ′_1, χ′′_2}}; χ′′(G) ≤ max{n_1, n_2} + 2(max{∆^B_1, ∆^B_2} + 1) if G is cobipartite, wherein ∆^B_i := max_{u ∈ V_i} d_{G[∂_G(V_i)]}(u) for i ∈ {1, 2}. Our algorithm for the cobipartite graphs runs in polynomial time. Our algorithm for the join graphs runs in polynomial time if P(G_1, G_2) is replaced by ∆_1 + ∆_2 + 1 or if it can be computed in polynomial time. We also prove the Total Colouring Conjecture for some subclasses of join graphs, such as some joins of indifference (unitary interval) graphs.

Paper Nr: 47
Title:

Impact of Service Interruptions and the Variability of Service Time in Queueing Systems: Numerical Investigations

Authors:

Yang Woo Shin and Dug Hee Moon

Abstract: In this paper, we consider the queueing systems with finite buffer and service interruptions. The effects of service interruptions and the variability of service time to measure of departure process such as the asymptotic mean and variance of the number of departures are investigated numerically. We find numerically so called interruption paradox or failure paradox that the departure rate of the system with service interruptions under preemptive-repeat-different policy can be greater than that of the system with reliable server and it increases as the interruption rate increases for the case of large variability of service time. The results give an insight for the effects of the system and may be helpful to design and control the more complex systems.

Paper Nr: 56
Title:

Wastewater Treatment Plant Design: Optimizing Multiple Objectives

Authors:

Roman Denysiuk, Isabel Espírito Santo and Lino Costa

Abstract: The high costs associated with the design of wastewater treatment plants (WWTPs) motivate the research in the area of modelling their construction and the water treatment process optimization. This work addresses different methodologies, which are based on defining and simultaneously optimizing several conflicting objectives, for finding the optimal values of the state variables in the plant design. We use an evolutionary many-objective optimization algorithm with clustering-based selection that proved effective in handling challenging optimization problems with a large number of objectives. The obtained results are promising and with physical meaning. It is shown that the overall WWTP design can be improved by coming up with appropriate formulation of the optimization problem and solving approach.

Paper Nr: 66
Title:

A Scalarized Augmented Lagrangian Algorithm (SCAL) for Multi-objective Optimization Constrained Problems

Authors:

Lino Costa, Isabel Espírito Santo and Pedro Oliveira

Abstract: In this paper, a methodology to solve constrained multi-objective problems is presented, using an Augmented Lagrangian technique to deal with the constraints and the Augmented Weighted Tchebycheff method to tackle the multi-objective problem and find the Pareto Frontier. We present the algorithm, as well as some preliminary results that seem very promising when compared to previous state-of-the- art work. As far as we know, the idea of incorporating an Augmented Lagrangian in multi-objective optimization is rarely used so, the obtained results are very encouraging to pursuit further in this line of investigation, namely with the tuning of the Augmented Lagrangian parameters as well as testing other algorithms to solve the subproblems or to handle the multi-objective problems. It is also our intention to investigate the resolution of problems with three or more objectives.

Area 2 - Applications

Full Papers
Paper Nr: 13
Title:

Game-theoretic Analysis of Air-cargo Allotment Contract

Authors:

Kannapha Amaruchkul

Abstract: Consider an air-cargo carrier and a freight forwarder, which may establish an allotment contract at the start of the season. The allotment size needs to be determined, before their stochastic demands materialize. The forwarder hopes to receive a discount rate, lower than the spot rate. The carrier hopes to increase capacity utilization by handling not only its own direct-ship demand but also the forwarder's demand. We formulate a Stackelberg game, in which the carrier is the leader and offers contract parameters such as the wholesale price and the refund rate for the unused allotment as well as the minimum allotment utilization. Given the carrier's offer, the forwarder decides how much to book as an allotment, in order to maximize its own expected profit. We analyze the game and identify conditions, in which an equilibrium contract coordinates the air-cargo chain. We show that the minimum allotment utilization is needed to construct a coordinating contract. In our numerical examples, we illustrate how to apply our approach to the case study of one of the biggest forwarders in Thailand. The contract can improve both parties' profits, compared to the scenario without any contract, where the forwarder purchases all capacity from the spot market.

Paper Nr: 32
Title:

Reengineering of the Emergency Service System under Generalized Disutility

Authors:

Marek Kvet and Jaroslav Janacek

Abstract: Emergency medical service system structure is defined by deployment of service providing centers, number of which is usually limited. The objective of the designer is to minimize the total discomfort of all system users. Thus, the problem often takes the form of a weighted p-median problem. Since population and demands for service change in time and space, current service center deployment may not meet the requirements of the users and service providers neither. In this paper, we introduce a mathematical model for system reengineering under the generalized disutility, which follows from the idea that the individual user’s disutility comes from more than one located service center. At the moment of current demand occurrence, the nearest service center may be unavailable due to satisfying another arisen demand. Presented approach constitutes an extension of previously developed methods, where only the nearest center was taken as a source of individual user’s demand satisfaction.

Paper Nr: 35
Title:

A Stochastic Multi-item Lot-sizing Problem with Bounded Number of Setups

Authors:

Etienne de Saint Germai, Vincent Leclère and Frédéric Meunier

Abstract: Within a partnership with a consulting company, we address a production problem modeled as a stochastic multi-item lot-sizing problem with bounded numbers of setups per period and without setup cost. While this formulation seems to be rather non-standard in the lot-sizing landscape, it is motivated by concrete missions of the company. Since the deterministic version of the problem is NP-hard and its full stochastic version clearly intractable, we turn to approximate methods and propose a repeated two-stage stochastic programming approach to solve it. Using simulations on real-world instances, we show that our method gives better results than current heuristics used in industry. Moreover, our method provides lower bounds proving the quality of the approach. Since the computational times are small and the method easy to use, our contribution constitutes a promising response to the original industrial problem.

Paper Nr: 50
Title:

Computing a Multi-location Aircraft Fleet Mix

Authors:

Slawomir Wesolkowski, Gregory Patchell and Akshay Dwarkan

Abstract: The Canadian Armed Forces periodically examines aircraft, ship or ground vehicle fleets to determine if they need to reduce, keep the same or increase the number of platforms in their fleets. We adapt previous work on fleet estimation and multi-objective optimization to compute a Pareto-optimal set of fleets at multiple locations, taking into account mission scheduling. We apply our model, which uses a genetic algorithm based on NSGA-II, to a sample of notional scenarios to demonstrate the effectiveness of the approach.

Short Papers
Paper Nr: 36
Title:

Tackling Demand Stochasticity by Redistribution among Retailers in a Two-stage Distribution System

Authors:

Benedikt De Vos and Birger Raa

Abstract: This paper considers a two-stage distribution system consisting of a supplier supplying several retailers with stochastic demand rates. Replenishments by the supplier happen cyclically, based on average retailer demand rates. Hence, the considered distribution problem between the suppliers and its retailers is a Cyclic Inventory Routing Problem (CIRP), which we solve with a state-of-the-art heuristic solution method. To cope with the demand stochasticity, lateral transshipments can happen between retailers in each time period. We propose a redistribution policy that determines the quantities being redistributed through lateral transshipments based on the desired level of customer service the retailers want to reach (using the desired fill rate) and their actual inventory levels. The cost of the daily redistribution is determined by solving a Travelling Salesman Problem (TSP) covering the participating retailers. The potential benefits of the collaboration among retailers are analyzed by comparing the distribution costs, the redistribution costs, the inventory holding costs and the costs of lost sales at the retailers in different scenarios.

Paper Nr: 54
Title:

A New Model Proposal for Integrated Satellite Constellation Scheduling within a Planning Horizon given Operational Constraints

Authors:

M. J. Pinto, A. I. Barros, R. Noomen, P. H. A. J. M. van Gelder and T. Lamballais Tessensohn

Abstract: The operational use of satellite systems has been increasing due to technological advances and the reduced costs of satellites and their launching. As such it has become more relevant to determine how to better use these new capabilities which is reflected in an increase in application studies in this area. This work focuses on the problem of developing the scheduling of a constellation of satellites and associated ground stations to monitor different types of locations (targets) with different priorities for a given planning horizon. In order to address this problem we will propose a new model that considers explicitly the operational requirements of Brazilian relevant scenarios for a given planning horizon and target priority list. The methodology to be developed to solve this model will also be discussed.

Paper Nr: 55
Title:

Dealing with Perceived Fairness when Planning Doctor Shifts in Hospitals

Authors:

Renaud De Landtsheer, Gaëtan Delannay and Christophe Ponsard

Abstract: Producing planning of doctors’ roles, including night shifts, on-call shifts (doctor can be called back in case of need), and regular working day in a hospital is complex and it is often difficult to effectively address all real world constraints. Furthermore, the produced solution requires a very good user acceptance to be effectively deployed in production. This paper reports on the application of metaheuristics to solve a planning problem in an hospital and focuses on user acceptance aspects of an algorithm. One of the key aspects to ensure user acceptance is to ensure the comprehensibility of the delivered solution. This includes the understanding of both the algorithm itself and its executions. The algorithm is a composition of local search, greedy algorithms, tabu search, and a few additional metaheuristic principles, and proved both good and fast enough.

Posters
Paper Nr: 12
Title:

Assignment-based MIP Modeling for Solving a Selling Firm mTSP with Time Limit Constraints

Authors:

Mojahid Saeed Osman

Abstract: This paper presents a version of the multiple traveling salesmen problem with service time limit constraints and travel times. The time required to provide merchandising service at any outlet location is predetermined based on the customer type. The objective is to minimize the number of salesmen hired by a selling firm while visiting and providing services to all customers without exceeding salesmen’s allowed working times. The paper proposes an assignment-based mixed integer programming model for solving the salesmen problem of a selling firm that applies a sub-tour elimination restriction. A case example is presented for illustrating the applicability and suitability of the proposed approach for solving the problem tackled in this work.

Paper Nr: 30
Title:

Evaluating Green and Resilient Supplier Performance: AHP-Fuzzy Topsis Decision-Making Approach

Authors:

Ahmed Mohammed, Irina Harris, Anthony Soroka, Naim Mohamed and Tim Ramjaun

Abstract: This paper presents an approach for evaluating and ranking suppliers with respect to their traditional, green and resilience (TGR) characteristics. A set of criteria/sub-criteria were identified within a unified framework and their relative importance weighted using the analytical hierarchy process (AHP) algorithm. In addition, the suppliers were evaluated and ranked based on their performance towards the identified TGR criteria using the fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) algorithm. The applicability and effectiveness of the proposed approach was proved through a real case study by revealing a comparatively meaningful ranking of suppliers. The study provides a noteworthy aid to management who understand the necessity of building supply chain resilience while concurrently pursuing ‘go green’ responsibilities.

Paper Nr: 33
Title:

Reengineering of the Emergency Service System from the Point of Service Provider

Authors:

Jaroslav Janacek and Marek Kvet

Abstract: An emergency service system design is usually worked up by a system administrator, who acts on behalf of the public. Applied objective is either minimal disutility perceived by an average user or disutility perceived by the worst situated user. This paper deals with a completely different case, when partial reengineering is suggested by one of the private service providers running a considerable portion of the current service centers. The provider tries to maximize his profit subject to the system administrator’s rules, which should protect public from worsening of their access to the service. We model the provider’s behavior and study efficiency of the administrator’s rules.

Paper Nr: 41
Title:

Dynamic Linear Assignment for Pairing Two Parts in Production - A Case Study in Aeronautics Industry

Authors:

Clémence Bisot

Abstract: In some manufacturing industries, the task of assembling two parts is a time-consuming step in production. Bonding can be more or less easy depending on the parts relative geometry. In this case, it becomes interesting to carefully choose the two pieces to be paired among available parts. As one does not know exactly the geometrical characteristics of the items that will be produced in the future, the problem of wisely choosing, over the long haul, the pairs to be bonded is dynamic. Minimizing the cost of pairing operation can be formulated as a dynamic linear assignment problem. This paper presents different heuristics used to solve the dynamic linear assignment problem in the framework of a specific application in the aeronautics industry. The article highlights how strong characteristics of the case study are used to choose adapted heuristics.

Paper Nr: 49
Title:

The Systemic Implications of Emergent Strategic Objectives in Complex Planning Situations

Authors:

Christine Große

Abstract: This paper develops a model for analysing systemic implications of strategic objectives in the context of national emergency response planning for the case of an electrical power shortage. Drawing on evidence from the Swedish approach, STYREL, the study emphasises the need for a thorough consideration of the various interests that are involved in such a complex system of national multi-level planning. This model provides a novel approach for analysing strategic objectives in complex planning environments, thereby offering a context for a constructive dialogue about strategic objectives, reachable goals and appropriate means among actors who are involved in such planning as well as the stakeholders it affects. Even beyond national critical infrastructure protection (CIP), the contribution of this paper is twofold: it outlines a complex problem for operations research in general and suggests a systematic approach for examining strategic objectives in complex planning environments in particular. Hence, this paper encourages a discussion of systemic implications of these various interests and an enhancement of collaboration and mutual understanding to facilitate decision-making in public and private strategic management.