Hybrid quantum-behaved particle swarm algorithm for nonlinear complementary problems

Tiefeng Zhu, Xueying Liu

Abstract

Combining amultiplier penalty functionmethod of dealingwith constraints using the quantumparticle swarmoptimization (QPSO) algorithm, a hybrid QPSO algorithm is proposed for solving nonlinear complementary problems. This method utilizes the advantages of the QPSO and the multiplier penalty function method. The non-feasible particles produced in the iterative process are dealtwith using the multiplier penalty function method to produce feasible particles. Numerical experiments show that the proposed algorithm is effective.