Chaotic lightning search algorithm

Abstract

Metaheuristics have proven their efficiency in treating complex optimization problems. Generally, they produce good results quite close to optimal despite some weaknesses such as premature convergence and stagnation in the local optima. However, some techniques are used to improve the obtained results, one of them is the adoption of chaos theory. Including chaotic sequences in metaheuristics has proven its efficiency in previous studies by improving the performance and quality of the results obtained. In this study, we propose an improvement of the metaheuristic lightning search algorithm (LSA) by using chaos theory. In fact, the idea is to replace the values of random variables with a chaotic sequences generator. To prove the success of the metaheuristic—chaos theory association, we tested five chaotic version of lightning search algorithm on a benchmark of seven functions. Experimental results show that sine or singer map are the best choices to improve the efficiency of LSA, in particular with the lead projectile update.