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 Schedule
			| Thursday, 30 January
 |  | 08:30-09:10 | Welcome-registration-coffee | B14-B15-B16 |  | 09:10-09:30 | Opening session | Amphi Cuccaroni |  | 09:30-10:30 | Plenary session  - Adam Letchford (Chair: Martine Labbé) | Amphi Cuccaroni |  | 10:30-11:20 | Coffee break | B14-B15-B16 |  | 11:20-12:40 | Parallel sessions |  |  | Multi-objective Optimization Chair: Sara Tari
 Room: E501
 | Health-care Chair: Véronique François
 Room: E502
 | Public Transportation Chair: Javier Duran Micco
 Room: E503
 | Global Optimization Chair: Olivier Rigal
 Room: E601
 | Analytics 1 Chair: Rafael Van Belle
 Room: E602
 |  | 12:40-14:10 | Lunch/ORBEL Board meeting | B14-B15-B16/E501 |  | 14:10-15:10 | Parallel sessions |  |  | Air, Rail and Multimodal Transportation Chair: Paola Paregrini
 Room: E501
 | Game Theory Chair: Lotte Verdnock
 Room: E502
 | Transportation of People Chair: Yves Molenbruch
 Room: E503
 | Multi-level Optimization Chair: Concepcion Dominguez
 Room: E601
 | Analytics 2 Chair: Vedavyas Etikala
 Room: E602
 |  | 15:10-15:50 | Coffee break | B14-B15-B16 |  | 15:50-16:40 | Parallel sessions |  |  | Sport Timetabling Chair: Dries Goossens
 Room: E501
 | Project Management and Scheduling Chair: Fan Yang
 Room: E502
 | Rich Routing and Graphs Chair: Alexandre Bontems
 Room: E503
 | Logistics Chair: Yuan Yuan
 Room: E601
 | Analytics 3 Chair: Jari Peeperkorn
 Room: E602
 |  | 16:50-17:30 | ORBEL general assembly | Amphi Cuccaroni |  | 19:00-20:00 | Cocktail | Bar Zango |  | 20:30-23:00 | Dinner | La Terrasse des Ramparts |  | Friday, 31 January
 |  | 09:30-10:30 | Plenary session - Miguel F. Anjos (Chair: Luce Brotcorne) | Amphi Cuccaroni |  | 10:30-11:20 | Coffee break | B14-B15-B16 |  | 11:20-12:40 | Parallel sessions |  |  | Automatic Configuration and Metaheuristics Analysis Chair: Kenneth Sorensen
 Room: E501
 | Real Life and Integrated Problems Chair: Jeroen Belien
 Room: E502
 | Warehouse Management Chair: Harol Mauricio Gamez
 Room: E601
 | Analytics 4 Chair: Noureddine Kouaissah
 Room: E602
 |  | 12:40-14:10 | Lunch | B14-B15-B16 |  | 14:10-15:10 | Parallel sessions |  |  | Orbel Award Chair: Jeroen Belien
 Room: E501
 | Optimization Chair: Julien Dewez
 Room: E502
 | Trucking Optimization Chair: Hatice Çalik
 Room: E601
 | Analytics 5 Chair: Diego Olaya
 Room: E602
 |  | 15:10-15:50 | Coffee break | B14-B15-B16 |  | 15:50-16:50 | Parallel sessions |  |  | Learning and Optimization Chair: Johan Van Kerckhoven
 Room: E501
 | Lot-sizing and Inventory Chair: Philippe Chevalier
 Room: E502
 | Rich Routing Chair: Cristian Aguayo
 Room: E601
 |  | 17:00-17:15 | ORBEL award and closing session | Amphi Cuccaroni |  | 17:15-18:30 | Closing cocktail | B14-B15-B16 |  | 
 |  Thursday 11:20 - 12:40 Multi-objective Optimization
 Room E501 - Chair: Sara Tari
 
 Thursday 11:20 - 12:40 Health-care
 Room E502 - Chair: Véronique François
 
 Thursday 11:20 - 12:40 Public Transportation
 Room E503 - Chair: Javier Duran Micco
 
 Thursday 11:20 - 12:40 Global Optimization
 Room E601 - Chair: Olivier Rigal
 
 Thursday 11:20 - 12:40 Analytics 1
 Room E602 - Chair: Rafael Van Belle
 
 Thursday 14:10 - 15:10 Air, Rail and Multimodal Transportation
 Room E501 - Chair: Paola Pellegrini
 
 Thursday 14:10 - 15:10 Game Theory
 Room E502 - Chair: Lotte Verdnock
 
 Thursday 14:10 - 15:10 Transportation of People
 Room E503 - Chair: Yves Molenbruch
 
 Thursday 14:10 - 15:10 Multi-level Optimization
 Room E601 - Chair: Concepcion Dominguez
 
 Thursday 14:10 - 15:10 Analytics 2
 Room E602 - Chair: Vedavyas Etikala
 
 Thursday 15:50 - 16:50 Sport Timetabling
 Room E501 - Chair: Dries Goossens
 
 Thursday 15:50 - 16:50 Project Management and Scheduling
 Room E502 - Chair: Fan Yang
 
 Thursday 15:50 - 16:50 Rich Routing and Graphs
 Room E503 - Chair: Alexandre Bontems
 
 Thursday 15:50 - 16:50 Logistics
 Room E601 - Chair: Silia Mertens
 
 Thursday 15:50 - 16:50 Analytics 3
 Room E602 - Chair: Jari Peeperkorn
 
 Friday 11:20 - 12:40 Automatic Configuration and Metaheuristics Analysis
 Room E501 - Chair: Kenneth Sorensen
 
 Friday 11:20 - 12:40 Real Life and Integrated Problems
 Room E502 - Chair: Jeroen Belien
 
 Friday 11:20 - 12:40 Warehouse Management
 Room E601 - Chair: Harol Mauricio Gamez
 
 Friday 11:20 - 12:40 Analytics 4
 Room E602 - Chair: Noureddine Kouaissah
 
 Friday 14:10 - 15:10 Orbel Award
 Room E501 - Chair: Jeroen Belien
 
 Friday 14:10 - 15:10 Optimization
 Room E502 - Chair: Julien Dewez
 
 New Multi-Step Conjugate Gradient Method for Optimization Issam Moghrabi (Gulf University for Science and Technology)
 Co-authors: Issam A.R. Moghrabi
 Abstract:
 Conjugate Gradient methods (CG) are a class of methods for solving large unconstrained optimization problems. Their storage requirements are rather minimal compared to other methods as they do not store any matrices. Such methods have been used in a variety of domains to solve nonlinear optimization problems as well as systems nonlinear equations. The methods have proven their effectiveness in applications such as Image restoration using a conjugate gradient-based adaptive filtering and Brain Magnetic Resonance Images Segmentation. While such methods converge in at most n iterations on quadratic functions for exact line searches, they are also used to minimize non-quadratic functions and inexact line searches. In the context of minimizing non-quadratic functions, the methods need to be restarted when certain criteria is met  On the other hand, multi-step methods are secant-like techniques of the quasi-Newton type that, unlike the classical methods, construct nonlinear alternatives to the quantities in the so-called Secant equation.  Multi-step methods instead utilize data available from the m most recent iterations and thus create an alternative to the Secant equation with the intention of creating better Hessian approximation that induce faster convergence to the minimizer of the objective function f. The methods, based on reported numerical results published in several research papers related to the subject, have introduced substantial savings in both iteration and function evaluation counts. Encouraged by the successful performance of the methods, we explore in this paper using them in developing a new Conjugate Gradient (CG) algorithm. CG methods gain popularity on big problems and in situations when memory resources are scarce.  The numerical experimentations on the new method are encouraging and open venue for further investigation of such techniques to explore their merits in a multitude of applications. The method requires less storage to implement than other known methods. This saving in resources is especially appreciated on large problems. Other choices for the parameters used in the construction of the search directions are under consideration to determine whether the numerical performance of the method can be improved further. There also remains the issue of developing automatic restart criteria that provides appropriate switching among several options. The global convergence properties of such methods are also under study.
 
Constrained Binary Quadratic PRoblems? No.... There is EXPEDIS Nicolo Gusmeroli (TU Dortmund)
 Co-authors: Angelika Wiegele
 
Computing lower bounds on the nonngative rank using a nested polytopes formulation Julien Dewez (Université catholique de Louvain)
 Co-authors: François Glineur
 
 Friday 14:10 - 15:10 Trucking Optimization
 Room E601 - Chair: Hatiz Çalik
 
 Friday 14:10 - 15:10 Analytics 5
 Room E602 - Chair: Diego Olaya
 
 Friday 15:50 - 16:50 Learning and Optimization
 Room E501 - Chair: Jorik Jooken
 
 Friday 15:50 - 16:50 Lot-sizing and Inventory
 Room E502 - Chair: Philippe Chevalier
 
 Friday 15:50 - 16:50 Rich Routing
 Room E601 - Chair: Cristian Aguayo
 
 
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	  	|  | ORBEL  - Conference chairs: Diego Cattaruzza and Maxime Ogier 
 
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