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Keynote Lectures

The Power of Duality
Aharon Ben-Tal, Technion, Israel Institute of Technology, Israel

Brokering Insights: Or How to Stop Freaking Out About the Wrong Things
Aaron Burciaga, VP Data Science and Machine Learning, Booz Allen Hamilton, United States

On Some Smart Hybridized Heuristics and Local Search Programming
Abdelkader Sbihi, Normandie Univ, France


The Power of Duality

Aharon Ben-Tal
Technion, Israel Institute of Technology

Brief Bio
Aharon Ben-Tal is a Professor of Operations Research and former head of the MINERVA Optimization Center at the Faculty of Industrial Engineering and Management at the Technion – Israel Institute of Technology, and holder of the Dresner Chair.  He received his Ph.D. in Applied Mathematics from Northwestern University in 1973.  He has been a Visiting Professor at the University of Michigan, University of Copenhagen, Delft University of Technology, MIT, CWI Amsterdam, Columbia University and NYU.  His interests are in Continuous Optimization, particularly nonsmooth and large-scale problems, conic and robust optimization, as well as convex and nonsmooth analysis. Recently the focus of his research is on optimization problems affected by uncertainty. In the last 15 years, he has devoted much effort to engineering applications of optimization methodology and computational schemes. Some of the algorithms developed in the MINERVA Optimization Center are in use by Industry (Medical Imaging, Aerospace). He has published more than 130 papers in professional journals and co-authored three books:  Optimality in Nonlinear Programming:  A Feasible Direction Approach (Wiley-Interscience, 1981) Lectures on Modern Convex Optimization:  Analysis, Algorithms and Engineering Applications (SIAM-MPS series on optimization, 2001) and Robust Optimization (Princeton University press, 2009). Prof. Ben-Tal was Dean of the Faculty of Industrial Engineering and Management at the Technion (1989-1992) and (2011-2014).  He served as a council member of the Mathematical Programming Society (1994-1997).  He was Area Editor (Continuous Optimization) of Math. of  Operations Research (1993-1999), member of the Editorial Board of SIAM  J. Optimization, J. Convex Analysis, OR Letters, Mathematical Programming, Management Science, Math. Modeling and Numerical Analysis, European J. of Operations Research and Computational Management Science.  During 2012-2014, he was the Area Editor (Optimization) for Operations Research. From February 2015, he is Associate Editor for SIAM J. Optimization.
He gave numerous plenary and keynote lectures in international conferences.

In 2007, Professor Ben-Tal was awarded the EURO Gold Medal - the highest distinction of Operations Research within Europe.
In 2009, he was named Fellow of INFORMS.
In 2010, he was awarded the status of Distinguished Scientist by CWI (center for mathematics and computer science, The Netherlands).
In 2011, he received the IBM Faculty Award.
In 2015, he was named Fellow of SIAM
In 2016 he was awarded the Khachiyan Prize of INFORMS Optimization Society-   for lifetime achievements in the area of Optimization.
In 2017, the Operation Research Society of Israel (ORSIS) awarded him the lifetime achievement Prize.

As of April 2017, he has more than 19,500 citations (Google scholar).

The talk discusses the use of Duality Theory to greatly simplify the solution of otherwise much more intricate optimization problems. This is illustrated by considering applications arising in Robust Optimization,Statistical Information Theory, Design of Mechanical Structure and Machine Learning.



Brokering Insights: Or How to Stop Freaking Out About the Wrong Things

Aaron Burciaga
VP Data Science and Machine Learning, Booz Allen Hamilton
United States

Brief Bio
Aaron Burciaga is a VP Data Science and Machine Learning at Booz Allen Hamilton. Aaron is also a Reserve Marine Officer supporting the CIO Headquarters Marine Corps-Pentagon and a veteran of the Iraq War (Fallujah, Operation Iraqi Freedom). His technical interests are at the crossroads of advanced analytics, global logistics, and information management ("Internet of Things" (IoT) / "Big Data" / "Data Science"). He was elected to the CAP Analytics Certification Board (ACB) in 2015 and was nominated and elected to being the ACB Vice Chair for 2017. Aaron earned a M.S. in Operations Research from the Naval Postgraduate School and a B.S. from the United States Naval Academy.

Competitive organizations realize that analytics, across their enterprise system, is a required capability to compete effectively in today’s global economy. Yet, few have succeeded in capturing the deep business value and embedded processes they wanted or expected from their analytics investments. Many are failing to place analytics at the heart of the decision-making process, thereby limiting their ability to differentiate themselves in the marketplace.

So, what does challenge mean to enterprise systems and data science? In this talk, Aaron Burciaga CAP, Analytics Executive at Accenture, will share some useful and entertaining ways to develop an enterprise analytics programs to deliver the last mile and final dollar:
· Trading risk with analytic confidence
· Brokering insights to win customer and business share of mind
· Agile testing and adoption of emergent technologies and methods, including ML, AI, Quantum Computing



On Some Smart Hybridized Heuristics and Local Search Programming

Abdelkader Sbihi
Normandie Univ

Brief Bio
Abdelkader SBIHI is professor of Optimisation and Operations Management. He is Senior Researcher at ESLI (Graduate School of Industrial Engineering-Redon, France) and the Dean for Research at ESCEM-Tours (France). He is associate member of the Laboratoire de Mathématiques Appliquées du Havre (LMAH-Université Le Havre Normandie).
His main research is particularly concerned with the resolution and the development of algorithms {both exact and heuristic algorithms{ for hard combinatorial optimisation problems and especially for hard variants of the knapsack problem. His current research interests include the sparse routing problems, the Quality of Service with Service-Level Agreements in logistics networks and especially for the multi-actors multi-level supply chain optimisation. Abdelkader earned a M.S in Applied Mathematics with major in Operational Research, a MRes in Mathematical Modeling, a PhD in Computer Science and a Habilitation to Supervise Research (HDR) in Operational Research.

In algorithmic, a heuristic process usually allows to build approximate solutions with no guarantee of reaching the optimal solution. Also, generally a heuristic approach is designed for a particular problem, based on its proper structure without offering any guarantee as to the quality of the computed solution. However, a good heuristic's "technology" or "machinery" is also the result of a wide experience acquired in tailoring such methods of resolution for a number of optimisation problems that are usually derived from real life.

In practice, a heuristic is said to be efficient when it is tailor-focused for a specific problem. Nevertheless, there exists a set of such methods that can be easily adapted to certain problems or a class of problems via smart hybridizations. Thus taking advantage of these approaches may help tackling more hard optimisation problems.

In this keynote, we will revisit some specified hybridized heuristics techniques addressing some hard variants of the knapsack problem arising from the real life. We will show their hybridization efficiency. Also, we will talk on both the concepts of the domain local search and the local search programming which are witnessing a real development these last decades thanks to the computing technology more and more powerful.