Orthogonal Multiobjective Chemical Reaction Optimization Approach for the Brushless DC Motor Design

Abstract

The optimal design of a brushless direct-current motor (BLDCM) is a prevalent and practical issue in the field of magnetics. A major problem is to design a BLDCM so that it operates optimally in the sense of producing maximum efficiency with minimal material cost. Using the sizing model, a novel orthogonal multiobjective chemical reaction optimization (OMOCRO) algorithm is proposed to solve this problem. Chemical reaction optimization is a newly proposed heuristic algorithm, inspired by the interactions between molecules during chemical reactions. In our proposed OMOCRO, we employ a Pareto ranking scheme to deal with multiobjective optimization problems, and orthogonal experimental design is used in the initialization stage. Comparative experiments with nondominated sorting genetic algorithm and multiobjective particle swarm approach demonstrate that our proposed method is more competitive in handling complex optimization problems.