Solving multi-objective optimization problems by a bi-objective evolutionary algorithm

In this paper a novel model for multiobjective optimization problem is proposed first, in which the multiobjective optimization problem is transformed into a bi-objective optimization problem. In this bi-objective problem one objective is responsible for optimizing the quality of the solutions, and the other is to improve the distribution of the obtained nondominated solution set. Then a new crossover operator and selection scheme are designed. Based on these, a specific-designed evolutionary algorithm is presented. The simulations on five widely used benchmark problems are made and the results indicate that the proposed algorithm is efficient and outperforms the compared algorithms.