Treating Constraints as Objectives in Multiobjective Optimization Problems Using Niched Pareto Genetic Algorithm

摘要

In this paper, the constraints, in multiobjective optimization problems, are treated as objectives. The constraints are transformed in two new objectives: one is based on a penalty function nd the other is made equal to the number of violated constraints. o ensure the convergence to a feasible Pareto optimal ront, the constrained individuals are eliminated during the elitist rocess. The treatment of infeasible individuals required some relevant odifications in the standard Parks and Miller elitist technique. nalytical and electromagnetic problems are presented and he results suggest the effectiveness of the proposed approach.