Enhancing Reptile Search Algorithm Performance for the Knapsack Problem with Integration of Chaotic Map

José Barrera-García, Felipe Cisternas-Caneo, Broderick Crawford, Ricardo Soto, Marcelo Becerra-Rozas, Giovanni Giachetti, Eric Monfroy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This study investigates the binarization process of the Reptile Search Algorithm (RSA) using chaotic maps to solve the Knapsack Problem. We evaluate RSA, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO) using the S4 transfer function with four binarization strategies: standard, standard with chaotic maps, elitist, and elitist with chaotic maps. Experimental results show that standard binarization strategies, particularly RSA with standard binarization rule (STD) and RSA with standard binarization rule with a chaotic map (STD_SINE), consistently outperform elitist strategies across various Knapsack problem instances. Including chaotic maps, especially the sine chaotic map, slightly improves performance. Convergence analysis reveals that standard binarization ensures steady and strong convergence, while elitist binarization accelerates convergence but may risk settling on local optima early. This research highlights the importance of selecting appropriate binarization strategies and suggests further exploration of chaotic maps to enhance the performance of metaheuristic algorithms in solving binary combinatorial optimization problems.

Original languageEnglish
Title of host publicationAdvances in Soft Computing - 23rd Mexican International Conference on Artificial Intelligence, MICAI 2024, Proceedings
EditorsLourdes Martínez-Villaseñor, Gilberto Ochoa-Ruiz
PublisherSpringer Science and Business Media Deutschland GmbH
Pages70-81
Number of pages12
ISBN (Print)9783031755422
DOIs
Publication statusPublished - 2025
Event23rd Mexican International Conference on Artificial Intelligence, MICAI 2024 - Tonantzintla, Mexico
Duration: 21 Oct 202425 Oct 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15247 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference23rd Mexican International Conference on Artificial Intelligence, MICAI 2024
Country/TerritoryMexico
CityTonantzintla
Period21/10/2425/10/24

Keywords

  • Binarization Schemes
  • Chaotic Maps
  • Combinatorial Problems
  • Metaheuristics
  • Reptile Search Algorithm

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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