A Multi-Objective Evolutionary Algorithm Based on Orthogonal Design

A multi-objective evolutionary algorithm (MOEA), called orthogonal multi-objective evolutionary algorithm (OMOEA), is proposed in this paper. The idea of OMOEA is that an original niche (decision space) evolves first, and splits into a group of subniches according to the output niche-population of the evolution; then every subniche iterates the above operations so as to enhance the precision of the solutions. The main component of the new technique is the niche evolution procedure which uses a generalized design method for MOPs to locate a non-dominated set like the orthogonal design and uses the statistical optimal method for SOPs to locate optimal solution. Employed orthogonal design method and statistical method, the OMOEA can converge fast and yield evenly distributed solutions with high precision. The numerical results show that above algorithm performs better than SPEA and other MOEAs for MOPs with two objectives. For an engineering MOP with five objectives and seven constraints, the new technique finds the precise Pareto-optimal solutions which is unknown before.