Solving Engineering Optimization Design Problems Based on Improved JAYA Algorithm

In order to better solve the engineering design constrained optimization problem and further improve the global optimization and application ability of the JAYA algorithm, the JAYA algorithm based on multi role differential evolution strategy is proposed. Firstly, the cosine similarity strategy is introduced, the individual positions with high cosine similarity to the optimal individual are processed by rotation change operator and non-uniform mutation operator, which not only accelerates the convergence speed of the algorithm, but also enriches the diversity of the population; Then the multi role strategy is introduced to the individual location updating, and the symbiosis strategy and cauchy mutation mechanism are introduced to effectively balance and better meet the different needs of the algorithm for exploration and mining ability in different iterative periods, which improves the optimization performance of the algorithm; Finally, the pinhole-imaging opposition-based learning strategy is introduced, which expands the search range of the algorithm and further improves the convergence and accuracy of the algorithm. Through the simulation experiment of function extremum optimization of the multi algorithms on multiple dimensions of the 10 complex benchmark test functions and the optimization of 5 more challenging complex engineering design problems described in CEC2020, the test results clearly show that the proposed algorithm has significantly better optimization accuracy, convergence performance, solution stability, applicability and effectiveness to different problems, and it has obvious advantages in solving engineering design optimization problems. © 2023 Chinese Institute of Electronics. All rights reserved.