American Journal of Industrial Engineering
ISSN (Print): 2377-4320 ISSN (Online): 2377-4339 Website: Editor-in-chief: Ajay Verma
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American Journal of Industrial Engineering. 2020, 7(1), 14-25
DOI: 10.12691/ajie-7-1-3
Open AccessArticle

Multi-Objective Mixed Model Assembly Line Balancing Using Mixed Integer Linear Programming

Nafi Ahmed1, and Md. Sazzad Hossain Ador1

1Department of Mechanical & Production Engineering, Ahsanullah University of Science & Technology, Dhaka-1208, Bangladesh

Pub. Date: March 01, 2020

Cite this paper:
Nafi Ahmed and Md. Sazzad Hossain Ador. Multi-Objective Mixed Model Assembly Line Balancing Using Mixed Integer Linear Programming. American Journal of Industrial Engineering. 2020; 7(1):14-25. doi: 10.12691/ajie-7-1-3


Now a day’s Mixed-Model Assembly Line Balancing is becoming more and more popular for mass production system. In mass production, huge costs, time, equipment and manpower are involved. Therefore, to reduce those cost, time, equipment and manpower, Mixed-Model Assembly Line Balancing can be very useful. In Single Model Assembly Line Balancing, only one type of product or model can be produced. But in Mixed- Model Assembly Line Balancing, multiple objects or multiple products can be produced at the same time.Therefore, mixed model assembly line balancing can provide better results in optimizing these resources. Different type of methods can be used to solve Mixed-Model Assembly Line Balancing problem. However, we have used a framework of Mixed Integer Linear Programming to solve a mixed model assembly line problem for garments industry. The proposed model using the Mixed Integer Linear programming outperforms other traditional model for optimizing the set of resources. Moreover, in this paper cost, space and cycle time have been reduced simultaneously. And, a real life illustration has been shown for better understanding for the practitioner.

assembly line balancing mixed model assembly line mixed integer Linear Programming multi-objective optimization

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[1]  Hamta, N., Fatemi Ghomi, S. M. T., Jolai, F., & Akbarpour Shirazi, M, ‘‘A hybrid PSO algorithm for a multi-objective assembly line balancing problem with flexible operation times, sequence-dependent setup times and learning effect,’’ International Journal ofProduction Economics, Vol. 141(1), 99-111. 2013.
[2]  Kriengkorakot, Nuchsara & Pianthong, Nalin,‘‘The Assembly Line Balancing Problem: Review articles,’’The KKU Engineering Journal,Vol. 34, 133-140, 2007.
[3]  Thomopoulos, N. T. ‘‘Mixed Model Line Balancing with Smoothed Station Assignments’’Management Science, Vol. 16(9), 593-603, 2008.
[4]  Frazierb, V. ‘‘A heuristic for solving mixed-model line balancing problems with stochastic task durations and parallel stations’’ International journal of Production Economics,Vol. 5273 (97), 1997.
[5]  Gokce, H. ‘‘A goal programming approach to mixed-model assembly line balancing problem’’ International journal of Production Economics, Vol. 48, 177-185, 1997.
[6]  Evaluation, C., Line, A., & Heuristics, B.‘‘A Comparative Evaluation of Assembly Line Balancing Heuristics’’ International journal of Advanced manufacturing Technology,Vol. 15, 577-586, 1999.
[7]  Article, O. ‘‘A hybrid genetic algorithm approach to mixed-model assembly line balancing’’International journal of Advanced manufacturing Technology, Vol. 28(3), 337-341, 2006.
[8]  Akpınar, S., Bayhan, G. M., & Baykasoglu, A. ‘‘Hybridizing ant colony optimization via genetic algorithm for mixed-model assembly line balancing problem with sequence dependent setup times between tasks’’Applied Soft Computing Journal, Vol. 13(1), 574-589, 2013.
[9]  Simaria, A. S., & Vilarinho, P. M. ‘‘A genetic algorithm-based approach to the mixed-model assembly line balancing problem of type II’’ Computers and Industrial Engineering, Vol. 47(4), 391-407, 2004.
[10]  Özcan, U., & Toklu, B. ‘‘A tabu search algorithm for two-sided assembly line balancing’’International journal of Advanced manufacturing Technology, Vol. 43(7), 822-829, 2009.
[11]  Yagmahan, B. ‘‘Mixed-model assembly line balancing using a multi-objective ant colony optimization approach’’Expert Systems with Applications, Vol. 38(10), 12453-12461, 2011.
[12]  Baykasoglu, A., & Dereli, T. ‘‘Two-sided assembly line balancing using an ant-colony- based heuristic’’International journal of Advanced manufacturing Technology, Vol. 32, 582-588, 2008.
[13]  Kucukkoc, I., Zhang, D. Z., Buyukozkan, K., & Satoglu, S. I. ‘‘A mathematical model and artificial bee colony algorithm for the lexicographic bottleneck mixed-model assembly line balancing problem’’Journal of Intelligent Manufacturing, Vol. 30(8), 2913-2925, 2015.
[14]  Alghazi, A., & Kurz, M. E. ‘‘Mixed model line balancing with parallel stations, zoning constraints, and ergonomics’’ constraints, Vol. 23(8), 1-31, 2017.
[15]  Gamberini, R., Ã, A. G., & Rimini, B. ‘‘A new multi-objective heuristic algorithm for solving the stochastic assembly line re-balancing problem’’International journal of Production Economics, Vol. 102(2), 226-243, 2006.
[16]  Boysen, N., Fliedner, M., & Scholl, A. ‘‘Assembly line balancing: Which model to use when?’’International journal of Production Economics,Vol. 111(2), 509-528, 2008.
[17]  Chica, M., Bautista, J., & Cordón, Ó. ‘‘A multiobjective model and evolutionary algorithms for robust time and space assembly line balancing under uncertain demand’’ Omega, 2015.
[18]  Morshed, N., & Palash, K. S. ‘‘Assembly Line Balancing to ImproveProductivity using Work Sharing Method in Apparel Industry’’ Global Journal of Researchesin Engineering: G Industrial EngineeringVol. 14(3), 2014.
[19]  Delice, Y., & Kızılkaya, E. ‘‘A modified particle swarm optimization algorithm to mixed-model two-sided assembly line balancing’’Journal of Intelligent Manufacturing, 2014.
[20]  Lopes, T. C., Michels, A. S., Gustavo, C., Sikora, S.,& Magatão, L.‘‘Mixed-model assembly lines balancing with given buffers and product sequence: model, formulation comparisons, and case study’’ Annals of Operations Research, 2017.
[21]  Ramezanian, R., & Ezzatpanah, A. “Dynamic hoist scheduling problem with multi-capacity and worker assignment problem’’ Computers& industrial engineering, 2015.
[22]  Zhao, X., Hsu, C., Chang, P., & Li, L. ‘‘A genetic algorithm for the multi-objective optimization of mixed-model assembly line based on the mental workload’’Engineering Applications of Artificial Intelligence, 1-7, 2015.
[23]  Zahiri, B., Tavakkoli-moghaddam, R., & Rezaei-malek, M. ‘‘An MCDA-DEA approach for mixed-model assembly line balancing problem under uncertainty’’Journal of Intelligent and Fuzzy Systems, Vol. 30, 2737-2748, 2016.
[24]  Antunes, C. H., Martins, A. G., & Brito, I. S. ‘‘A multiple objective mixed integer linear programming model for power generation expansion planning’’Energy, Vol. 29(4), 613-627, 2004.
[25]  Razali, M. M., Ab Rashid, M. F. F., & Make, M. R. ‘‘A. Mathematical Modelling of Mixed-Model Assembly Line Balancing Problem with Resources Constraints’’IOP Conference Series: Materials Science and Engineering, Vol. 160(1), 2016.
[26]  Permata, L., & Hartanti, S. ‘‘Work Measurement Approach to Determine Standard Time in Assembly Line’’International Journal of Management and Applied Science, Vol. 2.1(10), 49-52, 2016.