Multi-objective tunicate search optimisation algorithm for numerical problems. (26th September 2022) - Sharma, Isha; Kumar, Vijay
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.