ORBEL 32

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Thursday, February 1
08:30-09:15Welcome
09:15-09:30Opening session
09:30-10:30Plenary session - Dominique Feillet (Chair: Yasemin Arda)
10:30-11:00Coffee break
11:00-12:20Parallel sessions
  Routing Problems
Chair: Pieter Vansteenwegen
Room: 138
Emergency operations scheduling
Chair: El-Houssaine Aghezzaf
Room: 130
Algorithm design
Chair: Gerrit Janssens
Room: 126
Multiple Objectives
Chair: Filip Van Utterbeeck
Room: 120
12:20-13:30Lunch
12:25-13:25ORBEL board meeting
13:30-14:50Parallel sessions
  Integrated logistics
Chair: Kris Braekers
Room: 138
Person transportation
Chair: Célia Paquay
Room: 130
Continuous models
Chair: Nicolas Gillis
Room: 126
Integer programming
Chair: Bernard Fortz
Room: 120
14:50-15:20Coffee break
15:20-16:20Parallel sessions
  Material handling and warehousing 1
Chair: Greet Vanden Berghe
Room: 138
Operations management
Chair: Roel Leus
Room: 130
Matrix factorization
Chair: Pierre Kunsch
Room: 126
 
16:30-17:10Parallel sessions
  Material handling and warehousing 2
Chair: Katrien Ramaekers
Room: 138
Routing and local search
Chair: An Caris
Room: 130
Traffic management
Chair: Joris Walraevens
Room: 126
Pharmaceutical supply chains
Chair: Bart Smeulders
Room: 120
17:15-18:15ORBEL general assembly
18:30-...Conference dinner

Friday, February 2
09:30-10:30Plenary session - Martin Savelsbergh (Chair: Yves Crama)
10:30-10:50Coffee break
10:50-12:10Parallel sessions
  Optimization in health care
Chair: Jeroen Beliën
Room: 138
Network design
Chair: Jean-Sébastien Tancrez
Room: 130
Local search methodology
Chair: Patrick De Causmaecker
Room: 126
ORBEL Award
Chair: Frits Spieksma
Room: 120
12:10-13:00Lunch
13:00-14:00Parallel sessions
  Production and inventory management
Chair: Tony Wauters
Room: 138
Logistics 4.0
Chair: Thierry Pironet
Room: 130
Data clustering
Chair: Yves De Smet
Room: 126
Collective decision making
Chair: Bernard De Baets
Room: 120
14:10-15:10Parallel sessions
  Sport scheduling
Chair: Dries Goossens
Room: 138
Discrete choice modeling
Chair: Virginie Lurkin
Room: 130
Data classification
Chair: Ashwin Ittoo
Room: 126
 
15:10-15:30Coffee break
15:30- 16:30Plenary session - Michel Bierlaire (Chair: Michaël Schyns)
16:30- 16:45ORBEL award and closing session
16:45-18:00Closing cocktail

Thursday 11:00 - 12:20 Routing Problems
Room 138 - Chair: Pieter Vansteenwegen

Thursday 11:00 - 12:20 Emergency operations scheduling
Room 130 - Chair: El-Houssaine Aghezzaf

Thursday 11:00 - 12:20 Algorithm design
Room 126 - Chair: Gerrit Janssens

Thursday 11:00 - 12:20 Multiple Objectives
Room 120 - Chair: Filip Van Utterbeeck

Thursday 13:30 - 14:50 Integrated logistics
Room 138 - Chair: Kris Braekers

Thursday 13:30 - 14:50 Person transportation
Room 130 - Chair: Célia Paquay

Thursday 13:30 - 14:50 Continuous models
Room 126 - Chair: Nicolas Gillis

Thursday 13:30 - 14:50 Integer programming
Room 120 - Chair: Bernard Fortz

Thursday 15:20 - 16:20 Material handling and warehousing 1
Room 138 - Chair: Greet Vanden Berghe

Thursday 15:20 - 16:20 Operations management
Room 130 - Chair: Roel Leus

Thursday 15:20 - 16:20 Matrix factorization
Room 126 - Chair: Pierre Kunsch

Thursday 16:30 - 17:10 Material handling and warehousing 2
Room 138 - Chair: Katrien Ramaekers

Thursday 16:30 - 17:10 Routing and local search
Room 130 - Chair: An Caris

Thursday 16:30 - 17:10 Traffic management
Room 126 - Chair: Joris Walraevens

Thursday 16:30 - 17:10 Pharmaceutical supply chains
Room 120 - Chair: Bart Smeulders

Friday 10:50 - 12:10 Optimization in health care
Room 138 - Chair: Jeroen Beliën

Friday 10:50 - 12:10 Network design
Room 130 - Chair: Jean-Sébastien Tancrez

Friday 10:50 - 12:10 Local search methodology
Room 126 - Chair: Patrick De Causmaecker

Friday 10:50 - 12:10 ORBEL Award
Room 120 - Chair: Frits Spieksma

    Friday 13:00 - 14:00 Production and inventory management
    Room 138 - Chair: Tony Wauters

    Friday 13:00 - 14:00 Logistics 4.0
    Room 130 - Chair: Thierry Pironet

    Friday 13:00 - 14:00 Data clustering
    Room 126 - Chair: Yves De Smet

    Friday 13:00 - 14:00 Collective decision making
    Room 120 - Chair: Bernard De Baets

    Friday 14:10 - 15:10 Sport scheduling
    Room 138 - Chair: Dries Goossens
    • Scheduling time-relaxed double round-robin tournaments with availability constraints
      David Van Bulck (Ghent University)
      Co-authors: Dries Goossens
    • Combined proactive and reactive strategies for round robin football scheduling
      Xia-jie Yi (Ghent University)
      Co-authors: Dries Goossens
    • A constructive matheuristic strategy for the Traveling Umpire Problem
      Reshma Chirayil Chandrasekharan (KU Leuven)
      Co-authors: Tulio A. M. Toffolo, Tony Wauters
      Abstract:
      Traveling Umpire problem (TUP) is a sports scheduling problem concerning the assignment of umpires to the games of a fixed round robin tournament. Introduced by Michael Trick and Hakan Yildiz in 2007, the problem abstracts the umpire scheduling problem in the American Major League Baseball (MLB). A typical season of MLB requires umpires to travel extensively between team venues and therefore, the primary aim of the problem is to assign umpires such that the total travel distance is minimized. Constraints that prevent assigning umpires to consecutive teams or team venues make the problem challenging. Instances comprising of 8 to 30 teams have been proposed and since the introduction, various exact and heuristic techniques have been employed to obtain near optimal solutions to small and medium-sized instances. However, exact techniques prove to be inefficient in producing high quality solutions for large instances of 26 to 32 teams which resembles the real world problem. The present work focuses on improving the solutions for the large instance and presents a decomposition based method implementing constructive matheuristics (CMH). A given problem is decomposed into subproblems of which IP formulations are solved sequentially to optimality. These optimal solutions of the subproblems are utilized to construct a solution for the full problem. Various algorithmic parameters are implemented and extensive experiments are conducted to study their effects in the final solution quality. The algorithm being constructive, parameters have to be tuned such that the solution for the current subproblem does not prevent the feasibility of the future subproblems. In addition, design parameters are utilized to ensure feasibility of constraints that cannot be locally evaluated with in each subproblem. Parameters such as size of the subproblems and amount of overlap between the subproblems are tuned such that the solution quality is maximized while the runtime lies within the benchmark time limit of 5 hours. Design parameters such as the objective function and future of subproblems ensure that the solution constructed from the optimal solutions of the subproblems continues to be feasible in terms of the full problem. The proposed method has been able to improve the current best solutions of all the large instances within the benchmark time limits. In addition, CMH is also able to improve solutions of two medium sized instances of 18 teams. Furthermore, CMH generates solutions those are comparable or better than the solutions generated by other similar heuristics. Experiments conducted so far on the TUP suggest the possibility of CMH being applied on other similar problems. Apart from the innovations in terms of design parameters that may improve the CMH algorithm, the CMH has the inherent property of getting faster with the evolution of better IP solvers. Insights on the applicability of CMH to similar optimization problems and the expected advantages or shortcomings may also be discussed.

    Friday 14:10 - 15:10 Discrete choice modeling
    Room 130 - Chair: Virginie Lurkin

    Friday 14:10 - 15:10 Data classification
    Room 126 - Chair: Ashwin Ittoo

     
     
      ORBEL - Conference chair: Prof. A. Arda - Platform: Prof. M. Schyns.