DHRDE: Dual-population hybrid update and RPR mechanism based differential evolutionary algorithm for engineering applications

Abstract

In this paper, an enhanced differential evolution algorithm based on dual population hybrid update and random population replacement strategy (namely RPR mechanism) is proposed, which is called DHRDE. DHRDE algorithm involves three key improvements, first, the elite reverse population is constructed according to the original population before the update phase to uncover more potential areas to be searched. Second, a perturbation mechanism is integrated into the DE/rand/2 approach of the differential evolution algorithm to bolster its search efficiency, two updating models are established using co-leadership of random and locally optimal individuals, and then dual-population hybrid update strategy is adopted to achieve all-round and multi-angle search. Thirdly, using RPR mechanism to operate multiple types of mutations on some populations further improves the convergence accuracy. In order to verify the effectiveness of the proposed algorithm, DHRDE is compared with a variety of different types of algorithms in multi-dimension of the CEC2017, CEC2020 and CEC2022 test set, and statistical analysis is performed by Wilcoxon rank sum test and Friedman test. The results show that DHRDE algorithm has better performance. DHRDE algorithm is also used to solve seven engineering design problems and three PV model parameter estimation problems, the optimization results show that DHRDE algorithm is suitable for different complex problems and has effectiveness. In addition, this paper establishes a smooth path planning model for multi-size robots, and uses DHRDE to solve the model, the results of five groups of simulation experiments show that DHRDE algorithm can provide robot moving trajectories with higher smoothness and shorter paths. Analyzing and comparing the fitness metrics through heat maps, the comparative study demonstrates that the DHRDE algorithm is more advantageous and stronger than other algorithms in solving the smooth path planning model for multi-size robots. The above results show that DHRDE algorithm has better performance and has great advantages and competitiveness in solving engineering application optimization problems.