DCMOGA: Distributed Cooperation model of Multi-Objective Genetic Algorithm
نویسندگان
چکیده
In the multi objective problems, the good Pareto optimum solutions should have the following characteristics; the solutions should be close to the real Pareto front, the solutions should not be concentrated but should be widespread and the solutions should have the optimum solutions of every single objective function. ”Distributed Cooperation model of Multi-Objective Genetic Algorithm (DCMOGA)” is a new mechanism of MOGA to derive the solutions that have the above characteristics. In DCMOGA, there are N + 1 sub populations (islands) when there are N objects. One of these groups is the group for finding the Pareto optimum solutions. This group is called a MOGA group. One of the other groups is the group for finding the optimum of ith objective function. These groups are called SOGA groups. Any GAs and MOGAs can be applied in the SOGA and MOGA groups respectively. The following steps are the procedure of the DCMOGA.
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