关键词: 表面贴装, 多目标优化, 差分算法, 灰熵关联分析

Abstract: To solve the multi-objective optimization problem of surface mounting, a multi-objective optimization model was established with feeders, placing sequence and changing times of the nozzles as sub-objectives. The concept of information entropy was introduced into the grey correlation analysis, and the grey entropy correlation analysis method was proposed. The original grey correlation degree was changed into grey entropy correlation degree. Based on grey entropy correlation analysis method, the grey entropy correlation degree functions of three sub-objectives were established and a multi-objective differential evolution algorithm with grey entropy correlation was presented. The coding method of real vector-location sequence was adopted to realize the application of differential evolution algorithm on surface mounting optimization. The experimental results indicated that at least two sub-objectives in Pareto optimal solutions of differential evolution algorithm were better than genetic algorithm, and the solution had better uniform distribution. Therefore, the multi-objective differential evolution algorithm with grey entropy correlation could solve the multi-objective optimization problem of surface mounting effectively.

Key words: surface mounting, multi-objective optimization, differential evolution algorithms, grey entropy correlation analysis