Research Article

Population-based local search algorithms for cross-domain search

Volume: 31 Number: 1 February 27, 2025
EN TR

Population-based local search algorithms for cross-domain search

Abstract

Population-based local search is a meta-heuristic algorithm combining the principles of the population-based search and the local search. This study presents an extensive comparison of two population-based local search approaches, specifically, the steady state memetic algorithm (SSMA) and a population-based iterated local search (PILS). To the best of our knowledge, PILS is proposed first for cross-domain search. Both approaches are implemented in Hyper-heuristics Flexible Framework (HyFlex) which contains different operators for different problem domains. The operators used in PILS and SSMA are the ones defined in HyFlex and the operator selection is done using two heuristic selection methods, namely, Simple Random and Reinforcement Learning with Tournament selection. The performance of the proposed methods with the selection methods is assessed over nine problem domains in HyFlex. The results reveal the success of the presented approaches for the crossdomain search.

Keywords

References

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Details

Primary Language

English

Subjects

Computer Vision and Multimedia Computation (Other)

Journal Section

Research Article

Authors

Publication Date

February 27, 2025

Submission Date

August 9, 2023

Acceptance Date

April 18, 2024

Published in Issue

Year 2025 Volume: 31 Number: 1

APA
Kiraz, B., & Corut Ergin, F. (2025). Population-based local search algorithms for cross-domain search. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 31(1), 86-97. https://izlik.org/JA54AC47TS
AMA
1.Kiraz B, Corut Ergin F. Population-based local search algorithms for cross-domain search. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2025;31(1):86-97. https://izlik.org/JA54AC47TS
Chicago
Kiraz, Berna, and Fatma Corut Ergin. 2025. “Population-Based Local Search Algorithms for Cross-Domain Search”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 31 (1): 86-97. https://izlik.org/JA54AC47TS.
EndNote
Kiraz B, Corut Ergin F (February 1, 2025) Population-based local search algorithms for cross-domain search. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 31 1 86–97.
IEEE
[1]B. Kiraz and F. Corut Ergin, “Population-based local search algorithms for cross-domain search”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 31, no. 1, pp. 86–97, Feb. 2025, [Online]. Available: https://izlik.org/JA54AC47TS
ISNAD
Kiraz, Berna - Corut Ergin, Fatma. “Population-Based Local Search Algorithms for Cross-Domain Search”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 31/1 (February 1, 2025): 86-97. https://izlik.org/JA54AC47TS.
JAMA
1.Kiraz B, Corut Ergin F. Population-based local search algorithms for cross-domain search. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2025;31:86–97.
MLA
Kiraz, Berna, and Fatma Corut Ergin. “Population-Based Local Search Algorithms for Cross-Domain Search”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, vol. 31, no. 1, Feb. 2025, pp. 86-97, https://izlik.org/JA54AC47TS.
Vancouver
1.Berna Kiraz, Fatma Corut Ergin. Population-based local search algorithms for cross-domain search. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi [Internet]. 2025 Feb. 1;31(1):86-97. Available from: https://izlik.org/JA54AC47TS