Multi-objective tunicate search optimisation algorithm for numerical problems. (26th September 2022)

• Record Type: Journal Article
• Authors: Sharma, Isha; Kumar, Vijay
• Is Part Of: International journal of intelligent engineering informatics. Volume 10:Number 2(2022)
• Page Start: 119
• Page End: 144
• Publication Date: 2022-09-26
• Subjects: tunicate search optimiser -- optimisation -- swarm intelligence -- multi-objective optimisation -- benchmark test functions -- spread -- spacing -- generational distance -- pareto optimal -- pareto front; Artificial intelligence -- Engineering applications -- Periodicals; Engineering -- Computer programs -- Periodicals; Knowledge management -- Periodicals; 620.0028563
• Languages: English
• ISSNs: 1758-8715

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.