IYDSE: Ameliorated Young’s double-slit experiment optimizer for applied mechanics and engineering

Abstract

The Young’s Double-Slit Experiment (YDSE) optimizer is a newly developed swarm intelligence algorithm inspired by Young’s double-slit experiment that reveals the wave nature of light. Due to its simple structure and efficiency, the researchers employed the algorithm to address real-world optimization problems in multiple domains. However, in large-scale mechanical and engineering applications, it still needs to balance exploration and exploitation effectively and easily fall into local optimum. Therefore, in order to ameliorate these shortcomings, a multi-strategy improved YDSE optimizer named IYDSE is developed in this study. In IYDSE, introducing the Bernoulli map strategy ensures a higher quality initial population in the initialization, thus improving the convergence speed. Then, Levy flight is utilized as a local development engine to avoid local search stagnation of the optimal solution during optimization. In addition, mirror reflection learning is designed to enhance group diversity. Finally, the information entanglement strategy is introduced to enhance the information exchange between light and dark fringes, thus balancing the exploration-development capability. The superiority of the proposed IYDSE is comprehensively demonstrated by comparing it with state-of-the-art algorithms on the CEC2019 and CEC2020 test suites, respectively. Meanwhile, the practicability of IYDSE is also verified by solving five specific engineering design cases and 50 different types of engineering optimization suites. Finally, the IYDSE algorithm is applied to three truss topology optimization problems. The experimental results demonstrate the applicability and development potential of the proposed algorithm in practical engineering applications. Therefore, IYDSE is potentially an effective and competitive algorithm for solving applied mechanics and engineering.