An Improved Meerkat Clan Algorithm for Solving 0-1 Knapsack Problem

     Meerkat Clan Algorithm (MCA) is a nature-based metaheuristic algorithm which imitates the intelligent behavior of the meerkat animal. This paper presents an improvement on the MCA based on a chaotic map and crossover strategy (MCA-CC). These two strategies increase the diversification and inten...

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Bibliographic Details
Published inIraqi journal of science pp. 773 - 784
Main Authors Hussein, Samer Alaa, Yousif, Ahmed Yacoub
Format Journal Article
LanguageEnglish
Published 27.02.2022
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Summary:     Meerkat Clan Algorithm (MCA) is a nature-based metaheuristic algorithm which imitates the intelligent behavior of the meerkat animal. This paper presents an improvement on the MCA based on a chaotic map and crossover strategy (MCA-CC). These two strategies increase the diversification and intensification of the proposed algorithm and boost the searching ability to find more quality solutions. The 0-1 knapsack problem was solved by the basic MCA and the improved version of this algorithm (MCA-CC). The performance of these algorithms was tested on low and high dimensional problems. The experimental results demonstrate that the proposed algorithm had overcome the basic algorithm in terms of solution quality, speed and gained optimality with low dimensional problems. Furthermore, in high dimensional problems, it has competitive results in comparison with the other algorithms.
ISSN:0067-2904
2312-1637
DOI:10.24996/ijs.2022.63.2.32