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

Authors

  • Samer Alaa Hussein Information Technology Center, University of Technology, Baghdad, Iraq
  • Ahmed Yacoub Yousif Information Technology Center, University of Technology, Baghdad, Iraq

DOI:

https://doi.org/10.24996/ijs.2022.63.2.32

Keywords:

Optimization, Metaheuristic, Meerkat Clan Algorithm, Knapsack Problem

Abstract

     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.

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Published

2022-02-27

Issue

Section

Computer Science

How to Cite

An Improved Meerkat Clan Algorithm for Solving 0-1 Knapsack Problem. (2022). Iraqi Journal of Science, 63(2), 773-784. https://doi.org/10.24996/ijs.2022.63.2.32

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