TY - JOUR
ID - 246
TI - A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers
JO - Journal of Optimization in Industrial Engineering
JA - JOIE
LA - en
SN - 2251-9904
AU - Fattahi, Parviz
AU - Samouei, Parvaneh
AD - Bu-Ali Sina University
Y1 - 2016
PY - 2016
VL - 9
IS - 20
SP - 9
EP - 18
KW - Mixed-model assembly line balancing
KW - Multi-Objective Optimization
KW - different skilled workers
KW - particle swarm optimization
KW - simulated annealing
DO - 10.22094/joie.2016.246
N2 - This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the workerâ€™s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorithm. This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the workerâ€™s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorithm
UR - http://www.qjie.ir/article_246.html
L1 - http://www.qjie.ir/article_246_f4a11b067ffa0ea046885a8261301508.pdf
ER -