Efficient iterated local search based metaheuristic approach for solving sports timetabling problems of International Timetabling Competition 2021

I. Gusti Agung Premananda (), Aris Tjahyanto () and Ahmad Mukhlason ()
Additional contact information
I. Gusti Agung Premananda: Institut Teknologi Sepuluh Nopember (ITS)
Aris Tjahyanto: Institut Teknologi Sepuluh Nopember (ITS)
Ahmad Mukhlason: Institut Teknologi Sepuluh Nopember (ITS)

Annals of Operations Research, 2024, vol. 343, issue 1, No 15, 427 pages

Abstract: Abstract Sports timetabling is a complex and challenging problem. The latest open benchmark dataset for the sport timetabling problem is from the International Timetabling Competition (ITC) 2021. Due to its complexity, only a few approaches have successfully generated feasible solutions for the problems in this dataset, as reported in scientific literature. To the best of our knowledge, there is only one study in the literature that has successfully generated feasible solutions for all 45 problems in the dataset. In this paper, we propose our novel efficient algorithm based on the Iterated Local Search algorithm to solve the ITC 2021 benchmark dataset. Unlike prior successful approaches that combined metaheuristics with an exact approach, our proposed approach is solely metaheuristic. Our contribution includes the design of strategies for both perturbation and local search phases, coupled with the integration of shuffling strategies. The experimental results show that our proposed algorithm is remarkably successful in generating feasible solutions for all 45 problems present in the ITC 2021 dataset.

Keywords: Sports timetabling; ITC 2021; Iterated local search; Metaheuristic (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10479-024-06285-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:343:y:2024:i:1:d:10.1007_s10479-024-06285-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1007/s10479-024-06285-x

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().