Comparative Study of Krill Herd, Firefly and Cuckoo Search Algorithms for Unimodal and Multimodal Optimization

Abstract

Today, in computer science, a computational challenge exists in finding a globally optimized solution fro m an enormously large search space. Various meta-heuristic methods can be used for finding the solution in a large search space. These methods can be exp lained as iterative search processes that efficiently perform the exp loration and exp loitation in the solution space. In this context, three such nature inspired meta-heuristic algorith ms namely Krill Herd Algorith m (KH), Firefly Algorith m (FA) and Cuckoo search Algorithm (CS) can be used to find optimal solutions of various mathemat ical optimization problems. In this paper, the proposed algorithms were used to find the optimal solution of fifteen unimodal and mult imodal benchmark test functions commonly used in the field of optimization and then compare their performances on the basis of efficiency, convergence, time and conclude that for both unimodal and mu ltimodal optimization Cuckoo Search Algorith m v ia Lévy flight has outperformed others and for mu ltimodal optimization Krill Herd algorith m is superior than Firefly algorith m but for un imodal optimization Firefly is superior than Krill Herd algorithm.