A Comparative Analysis of Application of Genetic Algorithm and Particle Swarm Optimization in Solving Traveling Tournament Problem (TTP)

Abstract

Traveling Tournament Problem (TTP) has been a major area of research due to its huge application in developing smooth and healthy match schedules in a tournament. The primary objective of a similar problem is to minimize the travel distance for the participating teams. This would incur better quality of the tournament as the players would experience least travel; hence restore better energy level. Besides, there would be a great benefit to the tournament organizers from the economic point of view as well. A well constructed schedule, comprising of diverse combinations of the home and away matches in a round robin tournament would keep the fans more attracted, resulting in turnouts in a large number in the stadiums and a considerable amount of revenue generated from the match tickets. Hence, an optimal solution to the problem is necessary from all respects; although it becomes progressively harder to identify the optimal solution with increasing number of teams. In this work, we have described how to solve the problem using Genetic algorithm and particle swarm optimization.

Authors and Affiliations

Avijit Haldar, Shyama Mondal, Alok Mukherjee, Kingshuk Chatterjee

Keywords

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  • EP ID EP724399
  • DOI https://doi.org/10.61797/ijbic.v1i2.168
  • Views 81
  • Downloads 0

How To Cite

Avijit Haldar, Shyama Mondal, Alok Mukherjee, Kingshuk Chatterjee (2022). A Comparative Analysis of Application of Genetic Algorithm and Particle Swarm Optimization in Solving Traveling Tournament Problem (TTP). International Journal of Bioinformatics and Intelligent Computing, 1(2), -. https://europub.co.uk/articles/-A-724399