A Sport Tournament Scheduling by Genetic Algorithm with Swapping Method

TL;DR

This paper presents a genetic algorithm with a swapping method to optimize scheduling in the mirrored Traveling Tournament Problem, effectively minimizing total travel distances and outperforming existing solutions.

Contribution

The study introduces a novel genetic algorithm approach with a swapping method specifically designed for the mirrored Traveling Tournament Problem, achieving near-optimal travel minimization.

Findings

Solutions are close to the theoretical lower bound.

The algorithm outperforms known results in most cases.

Effective reduction in total travel distances.

Abstract

A sport tournament problem is considered the Traveling Tournament Problem (TTP). One interesting type is the mirrored Traveling Tournament Problem (mTTP). The objective of the problem is to minimize either the total number of traveling or the total distances of traveling or both. This research aims to find an optimized solution of the mirrored Traveling Tournament Problem with minimum total number of traveling. The solutions consisting of traveling and scheduling tables are solved by using genetic algorithm (GA) with swapping method. The number of traveling of all teams from obtained solutions are close to the lower bound theory of number of traveling. Moreover, this algorithm generates better solutions than known results for most cases.