A Chaos Embedded Differential Evolution Algorithm for Multi-Objective Optimization.

In Multi-Objective Optimization, the problem of identifying the whole pareto-optimal set is very crucial. In this paper, we developed a new Multi-Objective Evolutionary technique. The new method incorporates Differential Evolution algorithm to Chaos search for better exploration, and so better quality of solution. In order to obtain more diversified solution set we used the well known Fitness Sharing method to adopt the size of the external archive maintained by the technique during search. Several test functions are employed for experiments. The simulation results show that the proposed algorithm is efficient. [ABSTRACT FROM AUTHOR]