TY - JOUR
ID - 83
TI - Sequencing Mixed Model Assembly Line Problem to Minimize Line Stoppages Cost by a Modified Simulated Annealing Algorithm Based on Cloud Theory
JO - Journal of Optimization in Industrial Engineering
JA - JOIE
LA - en
SN - 2251-9904
AU - Zamami Amlashi, Zaman
AU - Zandieh, Mostafa
AD - MSc, Faculty of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
AD - Assistant Professor, Department of Industrial Management, Management and Accounting, Shahid Beheshti University, Tehran, Iran
Y1 - 2011
PY - 2011
VL - Volume 4
IS - 8
SP - 9
EP - 18
KW - Sequencing problem
KW - Mixed-model assembly line
KW - Just-in-time production system
KW - Cloud theory
KW - simulated annealing
KW - Minimizing line stoppages
DO -
N2 - This research presents a new application of the cloud theory-based simulated annealing algorithm to solve mixed model assembly line sequencing problems where line stoppage cost is expected to be optimized. This objective is highly significant in mixed model assembly line sequencing problems based on just-in-time production system. Moreover, this type of problem is NP-hard and solving this problem through some classical approaches such as total enumeration or exact mathematical procedures such as dynamic programming is computationally prohibitive. Therefore, we proposed the cloud theory-based simulated annealing algorithm (CSA) to address it. Previous researches indicates that evolutionary algorithms especially simulated annealing (SA) is an appropriate method to solve this problem; so we compared CSA with SA in this study to validate the proposed CSA algorithm. Experimentation shows that the CSA approach outperforms the SA approach in both CPU time and objective function especially in large size problems.
UR - http://www.qjie.ir/article_83.html
L1 - http://www.qjie.ir/article_83_96ddd4455af4f1acf5518eaebaac91c1.pdf
ER -