关键词: 混流装配线, 演进平衡, 粒子群优化算法, 优化

Abstract: With the dynamic changes such as different customer needs,equipment updates and improvements in assembly process and technology,the assembly line needed to be constantly adjusted,even balanced again.Evolution balance factors were researched for Mixed-Model Assembly Line (MMAL) in many ways,and a method was proposed for MMAL evolution balancing.A balance mathematical model,in which the minimum cycle time,smoothness index between workstation stations and adjustment costs were as the optimization target was established for MMAL evolution and optimized through an Improved Particle Swarm Optimization (IPSO) algorithm simultaneously.To increase particle diversity and improve search speed,the inertia factor was updated by using the success rate of particle evolution in IPSO,in which the favorable information in non-optimal particles was added to the optimal particle in the group.The effectiveness and feasibility of the method were validated by optimizing assembly line balancing of a manufacturing enterprise.

Key words: mixed assembly line, evolution balancing, particle swarm optimization, optimization