Chaotic Charged System Search with a Feasible-Based Method for Constraint Optimization Problems

Abstract

Recently developed chaotic charged system search was combined to feasible-based method to solve constraint engineering optimization problems. Using chaotic maps into the CSS increases the global search mobility for a better global optimization. In the present method, an improved feasible-based method is utilized to handle the constraints. Some constraint design examples are tested using the new chaotic-based methods, and the results are compared to recognize the most efficient and powerful algorithm.

Chaotic cuckoo search

“…And recently, chaotic theory has found applications in the area of metaheuristics. Up to now, chaotic sequences have been combined with several metaheuristic algorithms, such as imperialist competitive algorithm (Talatahari et al 2012), FA (Gandomi et al 2013c), charged system search (Nouhi et al 2013), chaotic swarming of particles (CSP) (Kaveh et al 2014), BA (Gandomi and Yang 2014), KH algorithm (Wang et al 2014d), memetic DE algorithm (Jia et al 2011) and PSO (Gandomi et al 2013d).…”