A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assemblyline balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number ofstations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimizationof the total human cost for a given cycle time.In addition, the performance of proposed algorithm is evaluated against a set of test problemswith different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm(SA)in terms of the quality of objectivefunctions. Results show that the proposed algorithm performs well, and it can be used as an efficient algorithm.

کلیدواژه ها:

Mixed-model ، assembly line balancing problem (ALBP) ، Multi-objective optimization ، Different skilled workers ، Particle swarm optimization ، Simulated annealing