Handling the balance of operators in evolutionary algorithms through a weighted Hill Climbing approach-Reference-Cited by-同舟云学术

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Handling the balance of operators in evolutionary algorithms through a weighted Hill Climbing approach

Published:2024-06 Issue: Volume:294 Page:111784
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Rodríguez-Esparza Erick,Morales-Castañeda Bernardo,Casas-Ordaz Angel,Oliva Diego^ORCID,Navarro Mario A.,Valdivia Arturo,Houssein Essam H.^ORCID

Publisher

Elsevier BV

Reference58 articles.

1. Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces;Storn;J. Glob. Optim.,1997

2. J.J. Grefenstette, Genetic algorithms and machine learning, in: Proceedings of the Sixth Annual Conference on Computational Learning Theory, 1993, pp. 3–4.

3. Evolution strategies–a comprehensive introduction;Beyer;Nat. Comput.,2002

4. Handling stagnation through diversity analysis: A new set of operators for evolutionary algorithms;Morales-Castaneda,2022

5. Balancing exploration and exploitation with adaptive variation for evolutionary multi-objective optimization;Tan;European J. Oper. Res.,2009

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