Skip to Main Content
A general finding solution method was introduced to high dimension multi-objective hybrid discrete variables and the multi-objective was transformed into single object to be found with relative degree of grey incidences. The method could reasonably deal with value adopting problems of hybrid discrete variables in optimization design. A equal probability chaotic emigration operator was introduced for carrying out improvement on the fundamental genetic algorithm and the grey compound genetic algorithmic program for the multi-objective optimization of hybrid discrete variables was developed. The example of cylinder helix compression spring optimization design shows that the proposed algorithm has no special requirements on the characteristics of optimal designing problems and has a fairly good universal adaptability and a reliable operation of program with a strong ability of overall convergence.