关键词: 混流装配线排序问题, 多目标优化, 猫群算法

Abstract: Aiming at the different cost of each workstation's idle/overload in practical Mixed Model Assembly Line(MMAL),a multi-objective optimization model with the improved objective of minimum workstation's idle/overload total cost,production variation rate and total product set-up time was built based on traditional minimizing station's total idle/overload cost, and an improved multi-objective cat swarm optimization was designed to solve it.To improve the global searching ability in earlier stage and local ability in later stage of the algorithm,a method of cat behavior mode selection based on liner mixed ratio was proposed.An improved seeking mode which could generate wide range candidate was presented based on diversified searching operator to extend the search range and improve the global searching ability of the algorithm.The proposed algorithm was compared with Non-dominated Sorting Genetic Algorithm-Ⅱ(NSGA-Ⅱ),Multi-Objective Particle Swarm Optimization(MOPSO)and improved Strength Pareto Evolutionary Algorithm(SPEA2),and the results showed that the proposed algorithm had advantages on convergence of solutions,distributivity of solutions and search capabilities of Pareto solutions.The proposed algorithm was applied in an enterprise's Mixed Model Assembly Line Sequencing Problem(MMALSP),and the diversified choices were provided for workshop scheduling personnel decision,and the results were better than those of existing method on case assembly line.

Key words: mixed model assembly line sequencing problem, multi-objective optimization, cat swarm optimization