A real-coded multi-objective quantum-inspired evolutionary algorithm and its application

A real-coded multi-objective quantum evolutionary algorithm is proposed with the extension of a real-coded single-objective quantum evolutionary algorithm, and it is applied to the optimization design problem of low voltage large current vehicle-based generator. The update mechanism and intelligent search mechanism are improved for multi-objective problem solution. Meanwhile crowd distance and population mutation are also taken into considered. The proposed algorithm is applied to test functions with two objectives and three objectives. Simulation shows better performance both in convergence and distribution compared with NSGA-II. According to design requirements, motor efficiency and material costs are selected as objective functions, and then the multi-objective model of low voltage large current vehicle-based generator is established. Applying the proposed algorithm to the model, better designing schemes are obtained compared with original scheme. The validity of the algorithm is proved.