Bender's Cuts Guided Large Neighborhood Search for the Traveling Umpire Problem

Authors:
Michael A. Trick;Hakan Yildiz
Affiliations:
Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA ,15213, USA;Tepper School of Business, Carnegie Mellon University, Pittsburgh, PA ,15213, USA
Venue:
CPAIOR '07 Proceedings of the 4th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
Year:
2007

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Abstract

This paper introduces the use of Bender's Cuts to guide a Large Neighborhood Search to solve the Traveling Umpire Problem, a sports scheduling problem inspired by the real-life needs of the officials of a sports league. At each time slot, a Greedy Matching heuristic is used to construct a schedule. When an infeasibility is recognized Bender's cuts are generated, which guides a Large Neighborhood Search to ensure feasibility and to improve the solution.