Tabu particle swarm optimization for sequencing problems in mixed-model assembly lines

WENG Yao-wei， LU Jian-sha， DENG Wei
（College of Mechanical Engineering， Zhejiang University of Technology， Hangzhou 310014， China）

Abstract： In order to solve the sequencing problems in open-station mixed-model assembly lines，a mathematical model was established that considered two objectives：to minimize the utility time and keep average consumption rate of parts，and the tabu particle swarm optimization was proposed to solve the problem. Aiming at standard particle swarm optimization with an insufficient accuracy in late search and easy to fall into the local optimum，the tabu search algorithm was brought to establish the optimal particle research mechanism as well as improve the capacity to jump out from a local optimum point. A random weight updates was brought in to balance the global and local search ability. An example was given to test the algorithm. The results indicate that the algorithm can solve sequencing problems in mixed-model assembly lines successfully with an effective outcome.
Key words： particle swarm optimization（PSO）；mixed-model assembly line； tabu search； sequencing