A Complex-valued Encoding Seeker Optimization Algorithm for Constrained Engineering Problems

Abstract

This article comes up with a complex-valued encoding seeker optimization algorithm (CSOA) base on the multi-chain method for the constrained engineering optimization problems. The complex value encoding and a multi-link strategy are leaded by the seeker optimization algorithm (SOA). The complex value encoding method is an influential global optimization strategy, and the multi-link is an enhanced local search strategy. These strategies enhance the individuals’ diversity and avert fall into the local optimum. This article chose fifteen benchmark functions, four PID control parameter models, and six constrained engineering problems to test. According to the experimental results, the CSOA algorithm can be used in the benchmark functions, PID control parameters optimization, and optimization constrained engineering problems. Compared to particle swarm optimization (PSO), simulated annealing base on genetic algorithm (SA_GA), gravitational search algorithm (GSA), sine cosine algorithm (SCA), multi-verse optimizer (MVO), and seeker optimization algorithm (SOA), the optimization ability and robustness of CSOA are better.