A New Linear Optimization Technique Coupling Evolutionary Algorithm for Solving Multiobjective Optimization Problems

A New Linear Optimization technique coupling evolutionary algorithm for Solving Multiobjective Optimization Problems (NLEA) based on real-coded method is proposed after analyzing the drawbacks of existing evolutionary algorithms in this paper. One of the main advantages of the proposed approach is that search space of constrained dominance problems with high dimensions is compressed into two dimensions. NLEA has a linear fitness function in two dimension space so as to evaluate fitness of each individual fast in population. A crossover operator based on density function and a new mutation operator is developed to extend the search space and extract the better solution. In our tests, A few benchmark multi-objective optimization problems which divided into two groups are taken to test this algorithm. The numerical experiments show that proposed approach is feasible and effective, and provides good performance in terms of uniformity and diversity of solutions.