An advanced hybrid meta-heuristic algorithm for solving small- and large-scale engineering design optimization problems
Pooja Verma, Raghav Prasad Parouha · Journal of Electrical Systems and Information Technology · 2021
Abstract An advanced hybrid algorithm (haDEPSO) is proposed in this paper for small- and large-scale engineering design optimization problems. Suggested advanced, differential evolution (aDE) and particle swarm optimization (aPSO) integrated with proposedhaDEPSO. In aDE a novel, mutation, crossover and selection strategy is introduced, to avoid premature convergence. And aPSO consists of novel gradually varying parameters, to escape stagnation. So, convergence characteristic of aDE and aPSO provides different approximation to the solution space. Thus,haDEPSO achieve better solutions due to integrating merits of aDE and aPSO. Also inhaDEPSO individual population is merged with other in a pre-defined manner, to balance between global and local search capability. The performance of proposedhaDEPSO and its component aDE and aPSO are validated on 23 unconstrained benchmark functions, then solved five small (structural engineering) and one large (economic load dispatch)-scale engineering design optimization problems. Outcome analyses confirm superiority of proposed algorithms over many state-of-the-art algorithms.