An enhanced genetic algorithm with a new crossover operator for the traveling tournament problem

Abstract

This paper proposes an enhanced genetic algorithm (E-GA) with a new crossover operator for the well-known NP-hard traveling tournament problem (TTP). TTP is the problem of scheduling a feasible double round robin tournament that minimizes the total distances traveled by the teams. The proposed E-GA for TTP uses a new crossover operator based on sharing the best partial path teams among the schedules. Further, E-GA uses a variable neighborhood search as a subroutine to improve the intensification mechanism in GA. The proposed method is evaluated on publicly available standard benchmarks and compared with other techniques for TTP. The computational experiment shows that the proposed method could build interesting results comparable to other state-of-the-art approaches.