Reference point-based nondominated sorting multi-objective quantum-inspired evolutionary algorithm

Dick Sigmund, Jong-Hwan Kim

Abstract: Various kinds of evolutionary algorithms have been developed to solve multi-objective optimization problems. One of them is multi-objective quantum-inspired evolutionary algorithm (MQEA) which utilizes quantum computing concepts to search the solution space effectively. MQEA used nondominated sorting and crowding distance calculation as the selection operator. This paper proposes MQEA with another kind of selection operator. The proposed RN-MQEA uses reference point-based nondominated sorting approach as the selection operator, which is adopted from NSGA-III. In the computer simulations, RN-MQEA is found to provide more diverse solutions compared to MQEA and NSGA-III in solving the DTLZ test problems.