SURROGATE REPRODUCTION AND COMPLEX METHOD FOR HANDLING CONSTRAINTS IN OPTIMIZATION BY GENETIC ALGORITHM

This paper proposes surrogate reproduction and complex method for handling constraints in optimization by real-coded genetic algorithm. This reproduction considers both the fitness values and constraint function values calculated by surrogate function, which ensures potential designs to be chosen preferentially. Meanwhile, this paper improves the individual violating constraints using complex method, so the quality of the whole population is enhanced and the numbers of feasible design are increased. It is advantageous to the search of optimum solution. The classical examples show that the method proposed in this paper is feasible and effective.