Meta-heuristics meet sports: a systematic review from the viewpoint of nature inspired algorithms

Author:

Ariyaratne M.K.A.1,Silva R.M.2

Affiliation:

1. Department of Computer Science, Faculty of Applied Sciences , University of Sri Jayewardenepura , Nugegoda , Sri Lanka .

2. Department of Statistics, Faculty of Applied Sciences , University of Sri Jayewardenepura , Nugegoda , Sri Lanka .

Abstract

Abstract This review explores the avenues for the application of meta-heuristics in sports. The necessity of sophisticated algorithms to investigate different NP hard problems encountered in sports analytics was established in the recent past. Meta-heuristics have been applied as a promising approach to such problems. We identified team selection, optimal lineups, sports equipment optimization, scheduling and ranking, performance analysis, predictions in sports, and player tracking as seven major categories where meta-heuristics were implemented in research in sports. Some of our findings include (a) genetic algorithm and particle swarm optimization have been extensively used in the literature, (b) meta-heuristics have been widely applied in the sports of cricket and soccer, (c) the limitations and challenges of using meta-heuristics in sports. Through awareness and discussion on implementation of meta-heuristics, sports analytics research can be rich in the future.

Publisher

Walter de Gruyter GmbH

Subject

Biomedical Engineering,General Computer Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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3. Genetic algorithms for optimal control of a continuous model of a diabetic population;2022 IEEE 3rd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS);2022-12-01

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