Title: Multi-objective tunicate search optimisation algorithm for numerical problems

Authors: Isha Sharma; Vijay Kumar

Addresses: Department of Computer Science and Engineering, National Institute of Technology, Hamirpur, Himachal Pradesh-177005, India ' Department of Computer Science and Engineering, National Institute of Technology, Hamirpur, Himachal Pradesh-177005, India

Abstract: In this paper, a multi-objective version of recently developed tunicate swarm algorithm (TSA) is proposed. The multi-objective TSA (MOTSA) utilises the external archive to store the non-dominated solutions. The concept of roulette wheel mechanism is also incorporated in MOTSA for selection of non-dominated solutions. To demonstrate the effectiveness of MOTSA, it is evaluated on the well-known benchmark test functions. The proposed MOTSA is compared with four well-renowned multi-Objective optimisation algorithms and quantitatively analysed by using the performance measures. The experimental results reveal that the proposed MOTSA outperforms the existing techniques in terms of performance measures.

Keywords: tunicate search optimiser; optimisation; swarm intelligence; multi-objective optimisation; benchmark test functions; spread; spacing; generational distance; pareto optimal; pareto front.

DOI: 10.1504/IJIEI.2022.125859

International Journal of Intelligent Engineering Informatics, 2022 Vol.10 No.2, pp.119 - 144

Received: 09 Jun 2021
Accepted: 25 Sep 2021
Published online: 30 Sep 2022 *

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