Analysis of a constructive matheuristic for the traveling umpire problem
| Autor: | Reshma C. Chandrasekharan, Túlio A. M. Toffolo, Tony Wauters |
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| Rok vydání: | 2018 |
| Předmět: |
Mathematical optimization
Optimization problem Job shop scheduling Computer science Heuristic (computer science) 030229 sport sciences Time limit 01 natural sciences Constructive 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Benchmark (computing) Decision Sciences (miscellaneous) Algorithm design 0101 mathematics Integer programming Social Sciences (miscellaneous) |
| Zdroj: | Journal of Quantitative Analysis in Sports. 15:41-57 |
| ISSN: | 1559-0410 2194-6388 |
| DOI: | 10.1515/jqas-2017-0118 |
| Popis: | The Traveling Umpire Problem (TUP) is a combinatorial optimization problem concerning the assignment of umpires to the games of a fixed double round-robin tournament. The TUP draws inspiration from the real world multi-objective Major League Baseball (MLB) umpire scheduling problem, but is, however, restricted to the single objective of minimizing total travel distance of the umpires. Several hard constraints are employed to enforce fairness when assigning umpires, making it a challenging optimization problem. The present work concerns a constructive matheuristic approach which focuses primarily on large benchmark instances. A decomposition-based approach is employed which sequentially solves Integer Programming (IP) formulations of the subproblems to arrive at a feasible solution for the entire problem. This constructive matheuristic efficiently generates feasible solutions and improves the best known solutions of large benchmark instances of 26, 28, 30 and 32 teams well within the benchmark time limit. In addition, the algorithm is capable of producing feasible solutions for various small and medium benchmark instances competitive with those produced by other heuristic algorithms. The paper also details experiments conducted to evaluate various algorithmic design parameters such as subproblem size, overlap and objective functions. |
| Databáze: | OpenAIRE |
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