In this paper, we discuss multiobjective optimization problems solved by co-evolutionary algorithms. We present A Game model based coevolutionary algorithm (GMBCA) to solve this class of problems and its performance is analyzed in comparing its results with those obtained with four others algorithms. Finally, the GMBCA is applied to solve the nutrition decision making problem to map the Pareto-optimum front. The results in the problem show its effectiveness.
Citation:
Gaoping Wang, Yongji Wang, "A Game Model Based Co-evolutionary Algorithms for Multiobjective Optimization Problems," icicic, vol. 3, pp.312-315, First International Conference on Innovative Computing, Information and Control - Volume III (ICICIC'06), 2006