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Soft Computing

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03.05.2019 | Methodologies and Application

Integer cat swarm optimization algorithm for multiobjective integer problems

verfasst von: Shahid Ali Murtza, Ayaz Ahmad, Jawad Shafique

Erschienen in: Soft Computing | Ausgabe 3/2020

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Abstract

In the literature, several variants of cat swarm optimization (CSO) algorithm are reported. However, CSO for integer multiobjective optimization problems (MOPs) has not yet been investigated. Owing to the frequent occurrence of integer MOPs and their importance in practical design problems, in this work, we investigate a new CSO approach for solving purely integer MOPs. This new approach named as multiobjective integer cat swarm optimization (MO-ICSO) algorithm incorporates the modified version of the CSO algorithm for MOPs. This approach is comprised of the concepts of rounding the floating points to the nearest integer numbers and the probabilistic updating (PU) technique. It uses the idea of Pareto dominance for finding the non-dominated solutions and an external archive for storing these solutions. We demonstrate the power of this new approach via its quantitative analysis and sensitivity test of its several parameters using different performance metrics performed over multiobjective multidimensional knapsack problem and several standard test functions. The simulation results argue that the proposed MO-ICSO approach can be a better candidate for solving the integer MOPs.

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Titel: Integer cat swarm optimization algorithm for multiobjective integer problems
verfasst von: Shahid Ali Murtza
Ayaz Ahmad
Jawad Shafique
Publikationsdatum: 03.05.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 3/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-04023-1

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