A chance-constrained multi-objective model for final assembly scheduling in ATO systems with uncertain sub-assembly availability

Document Type : Research Paper


Department of Industrial Engineering, Faculty of Engineering, Yazd University, Yazd, Iran


A chance-constraint multi-objective model under uncertainty in the availability of subassemblies is proposed for scheduling in ATO systems. The on-time delivery of customer orders as well as reducing the company's cost is crucial; therefore, a three-objective model is proposed including the minimization of1) overtime, idletime, change-over, and setup costs, 2) total dispersion of items’ delivery times in customers’ orders, and 3) tardiness and earliness costs.In order to reduce the involved risk,the uncertainty in the subassembly availabilities is addressed via a chance-constrained programming. The lexicographic method is employed to solve the model. The performance and validity is then evaluated using the real data from an electrical company. Notably, the decision maker can draw the appropriate results by a priority establishment between the costs and delivery time objectives. Moreover, formulating the existing uncertainty in the subassembly availabilities helps avoiding delay in the orders’ completion dates. Finally, applying joint lot size policy leads to a more proper scheduling of assembly sequence.


Main Subjects

Axsäter, S. (2005). Planning order releases for an assembly system with random operation times.OR Spectrum, 27(2-3), 459-470.
Chang, H-J., Su, R-H., Yang, C-T., & Weng, M. W. (2012). An economic manufacturing quantity model for a two-stage assembly system with imperfect processes and variable production rate.Computers & Industrial Engineering, 63(1): 285-293.‏
Cheng, T. C. E., Gao, C., & Shen, h.(2011).Production planning and inventory allocation of a single-product assemble-to-order system with failure-prone machines. International Journal of Production Economics, 131(2): 604-617.‏
Chu, C., Proth, J-M., & Xie, X. (1993). Supply management in assembly systems. Naval Research Logistics,40(7):933-949.
Cniu, H. N., & Lin, T. M. (1988). An optimal lot-sizing model for multi-stage series/assembly systems.Computers & operations research, 15(5): 403-415.
DeCroix, G. A., Song, J-S.,& Zipkin, P. H. 2009. Managing an assemble-to-order system with returns.Manufacturing & service operations management, 11(1): 144-159.
Dolgui, A., & Ould-Louly, M-A. (2002). A model for supply planning under lead time uncertainty.International Journal of Production Economics, 78(2): 145-152.
Dolgui, A. B., Portmann, M. C., &Proth, J. M. (1996). A control model for assembly manufacturing systems.System Modelling and Optimization, 519-526.‏
DeCroix, G.A., & Zipkin, P. H.(2005). Inventory management for an assembly system with product or component returns.Management Science, 51(8): 1250-1265.
Elhafsi, M. (2009). Optimal integrated production and inventory control of an assemble-to-order system with multiple non-unitary demand classes. European Journal of Operational Research, 194(1): 127-142.
Elhafsi,M.,& Hamouda, E. (2015). Managing an assemble-to-order system with after sales market for components.European Journal of Operational Research, 242(3): 828-841.
Gurnani, H., Ram, A., & Lehoczky, J. (1996). Optimal order policies in assembly systems with random demand and random supplier delivery.IIE transactions,28(11): 865-878.
Hnaien, F., Delorme, X., & Dolgui, A. (2010). Multi-objective optimization for inventory control in two-level assembly systems under uncertainty of lead times.Computers & operations research, 37(11): 1835-1843.
Hnaien, F., Delorme, X., & Dolgui, A. (2009). Genetic algorithm for supply planning in two-level assembly systems with random lead times.Engineering Applications of Artificial Intelligence, 22(6): 906-915.
Horng, S-C., & Lin, S-S. (2017). Ordinal optimization based metaheuristic algorithm for optimal inventory policy of assemble-to-order systems.Applied Mathematical Modelling,42: 43-57.‏
Karaarslan, A. G., Kiesmüller, G. P., & De Kok, A. G. (2013). Analysis of an assemble-to-order system with different review periods.International Journal of Production Economics, 143(2): 335-341.
Kumar, A.(1989). Component inventory costs in an assembly problem with uncertain supplier lead-times.IIE transactions,21(2): 112-121.
Mokhtari, S., Madani, K., & Chang, N-B. (2012). Multi-criteria decision making under uncertainty: application to the California’s Sacramento-San Joaquin Delta problem.World Environmental and Water Resources Congress.‏
Olhager,J., and Wikner,J. (1998). A framework for integrated material and capacity based master scheduling.In Beyond Manufacturing Resource Planning (MRP II),3-20.
Proth, J. M., Mauroy, G., Wardi, Y., Chu, C., & Xie, X. L. (1997). Supply management for cost minimization in assembly systems with random component yield times.Journal of Intelligent Manufacturing, 8(5): 385-403.
Song, D. P., Hicks, C., & Earl, C. F. (2002). Product due date assignment for complex assemblies.International Journal of Production Economics, 76(3): 243-256.
Tang, O., & Grubbström, R. W.(2003). The detailed coordination problem in a two-level assembly system with stochastic lead times.International journal of production economics, 81-82(11): 415-429.
Wang,X.J. (2014). On Assemble-to-order Systems", PhD Thesis, McMaster University.‏
Wemmerlöv,U. (1984). Assemble-to-order manufacturing: implications for materials management.Journal of Operations Management,4(4): 347-368.
Xiao, Y., Chen, J., & Lee, C-Y. (2010). Optimal decisions for assemble-to-order systems with uncertain assembly capacity.International Journal of Production Economics, 123(1): 155-165.
Yano, C. A. (1987). Stochastic leadtimes in two-level assembly systems.IIE transactions, 19(4): 371-378.