A hybrid genetic–firefly algorithm for engineering design problems

Abstract Firefly algorithm (FA) is a new random swarm search optimization that modeled after movement and the mutual attraction of flashing fireflies. The number fitness comparisons attractions in FA varies depending on model. A large can induce oscillations, while small cause early convergence add to computational time complexity. This study aims offer H-GA–FA, hybrid combines two metaheuristic algorithms, genetic (GA) FA, overcome flaws combine benefits both algorithms solve engineering design problems (EDPs). In this system, which blends concepts GA individuals are formed generation not only by processes but also mechanisms prevent falling into local optima, introduce sufficient diversity solutions, make equilibrium between exploration/exploitation trends. On other hand, deal with violation constraints, chaotic process was utilized keep solutions feasible. proposed H-GA–FA tested well-known test contain set 17 unconstrained multimodal functions 7 constrained benchmark problems, where results have confirmed superiority overoptimization methods. Finally, performance investigated many EDPs. Computational show competitive better than