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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
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