Co-Operation of Biology-Related Algorithms for Constrained Multiobjective Optimization

Abstract

A modification of the self-tuning meta-heuristic, called Co-Operation of Biology Related Algorithms for multiobjective optimization problems COBRA-m is introduced. Its basic idea consists of a cooperative work of five well-known bionic algorithms such as Particle Swarm Optimization, Wolf Pack Search, the Firefly Algorithm, the Cuckoo Search Algorithm and the Bat Algorithm with the use of Pareto optimality theory. The performance of the mentioned algorithms as well as COBRA-m on the set of benchmark functions is reported. It was established that the proposed approach COBRA-m has performed either comparably or better than its component bionic algorithms. Then the method COBRA-m is modified for solving constrained multiobjective optimization problems. The proposed algorithm is first validated against a subset of test functions, and then applied to known multiobjective design problems such as welded beam design and disc brake design. Simulation results suggest that the proposed algorithm works effectively