The Application of Dominant-Recessive Diploid Codes in MOGA

When solving an optimal problem, different encoding method has an important effect on the performance of multi-objective genetic algorithm. This paper breaks the traditional binary coding ideas, introduces a new dominant-recessive diploid codes which applied in the MOGA. we analyses the impact on solution space by the binary multi-objective genetic algorithm and dominant-recessive diploid codes multi-objective genetic algorithm, which is operated by three basic operators of tournament selection, two-point crossing, and the basic bit mutation. Furthermore, by using the Numerical experiments of three Classic multi-objective optimization test functions, this algorithms and the efficient binary multi-objective algorithms named niched pare to genetic algorithms are compared. From the solution, we know that this paper´s algorithm is obviously superiors to the niched pare to genetic algorithm about the distribution, convergence of solution and the capability of anti-prematurity. Thus, it is interpreted that the algorithm is feasible from the aspects of theoretic analysis and numerical experiments, and the pare to solutions can be came to.