A hybrid constraint handling techniques based on differential evolution algorithm for constrained optimization problems
Li‐Yun Fu, Chengyun Zhang, Haibin Ouyang · 2021 China Automation Congress (CAC) · 2021
Many practical engineering problems can be transformed into constrained optimization problems (COPs) , scholars prefer to use evolutionary algorithms (EA) to deal with COPS. Differential evolution (DE) algorithm has strong global search and convergence ability than other EA, however, when dealing with COPs, the search ability of DE algorithm is affected by parameter setting and constraint handling technology (CHT) is needed. In this paper, an improved differential evolution algorithm with a new hybrid CHT (IDE-HCHT) is used to deal with COPs, at the same time, the hybrid CHT replaces the selection step of the DE algorithm, and improves the processing efficiency of the algorithm. To verify its superiority, CEC2017 benchmark function is tested by the novel IDE-HCHT, and two other start-of-the-art algorithms, LSHADE44, UDE. The results show that the proposed method shows better competitive performance against the two algorithms.