Trade-off Analysis for Multi-Objective Aggregate Production Planning

Navid Mortezaei, Norzima Zulkifli, Mehrbakhsh Nilashi


Aggregate production planning (APP) determines the best way to meet forecast demand in the intermediate future, often from 3 to 18 months ahead, by adjusting regular and overtime production rates, inventory level, labor levels, subcontracting and backorder rates, and other controllable variables. However, the majority of APP models have cost-related objectives, whereas non-cost objectives are often sought by managers. In this study, authors try to minimize total costs and maximize customer service simultaneously. It is shown there is a trade-off between these objectives. Authors propose a linear model for aggregate production planning problem. Then, the two- phase method solution, which takes both objectives into consideration, is used as an alternative objective. By solving the model, it was found that minimizing one objective results in an average loss of about 20% in the other objective. The two- phase method solution, on the other hand, results in a loss of 8% from the furthest objective and 7% from the closest objective.


Aggregate production planning, Customer service, Trade-off, Two-phase method

Full Text:

Abstract PDF


Chen, H. K., & Chou, H. W. (1996). Solving multiobjective linear programming problems—a generic approach. Fuzzy sets and systems, 82(1), 35-38.pp. 72-80.

Fung. Y. K, Tang. J, Wang. D, 2003,. Multi product aggregate production planning with fuzzy demand and fuzzy capacities. IEEE Transactions on systems, man and cybernetics-part A:system and humans, 33(3) 2003, 302-313.

Iris, C., & Cevikcan, E. (2014). A Fuzzy Linear Programming Approach for Aggregate Production Planning. In Supply Chain Management Under Fuzziness (pp. 355-374). Springer Berlin Heidelberg.

Jamalnia, A., & Feili, A. (2013). A simulation testing and analysis of aggregate production planning strategies. Production Planning & Control, 24(6), 423-448.

Li, B., Wang, H., Yang, J., Guo, M., & Qi, C. (2013). A belief-rule-based inference method for aggregate production planning under uncertainty. International Journal of Production Research, 51(1), 83-105.

Mortezaei, N., & Zulkifli, N. (2014). A Study on Integration of Lot Sizing and Flow Shop Lot Streaming Problems. Arabian Journal for Science and Engineering, 39(12), 9283-9300.

Mortezaei, N., Norzima, Z., Tang, S. H., & Rosnah, M. Y. (2014). Lot Streaming and Preventive Maintenance in a Multiple Product Permutation Flow Shop with Intermingling. In Applied Mechanics and Materials (Vol. 564, pp. 689-693).

Mortezaei, N., Zulkifli, N., Hong, T. S., & Yusuff, R. M. (2013). Multi-objective aggregate production planning model with fuzzy parameters and its solving methods. Life Science Journal, 10(4), 2406-2414.

Mortezaei, N.; Zulkifli, N.; Hong, T.S.; Yusuff, R.M.: Multi objective aggregate production planning model with fuzzy parameters and its solving methods. Life Science Journal. 10(4), 2406–2414 (2013).

Navid Mortezaei and Norzima Zulkifli, “Integration of Lot Sizing and Flow Shop Scheduling with Lot Streaming,” Journal of Applied Mathematics, vol. 2013, Article ID 216595, 9 pages, 2013. doi:10.1155/2013/216595

Ning, Y., Liu, J., & Yan, L. (2013). Uncertain aggregate production planning. Soft Computing, 17(4), 617-624.

Saad, G. H. (1990). Hierarchical production-planning systems: extensions and modifications. Journal of the Operational Research Society, 609-624.

Techawiboonwong. A, Yenradee .p, 2003. Aggregate production planning with workforce transferring plan for multiple product types. Journal of production planning & control 15(5), 447-458.

Zimmermann, H.J. Fuzzy programming and linear programming with several objective functions, Fuzzy sets and Systems 1 (1978) 45-55.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.