MCDM'11 - paper no. 8


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Mouna Mezghani , Taicir Loukil, Belaid Aouni


In the Aggregate Production Planning (APP) the manager considers simultaneously conflicting objectives such as total cost, inventories level, workforce fluctuation, and utilization level of the physical facility and equipment. The goals associated with these objectives may be uncertain in nature. The aim of this paper is to develop a goal programming (GP) model where the goals and the right-hand sides of constraints are random and normally distributed. The concept of satisfaction functions will be used for modeling the uncertainty as well as to explicitly integrate the manager preferences. The proposed model is applied to APP problem to generate the most satisfying aggregate plan.


Aggregate Production Planning; Goal Programming; Satisfaction Functions.

Reference index:

Mouna Mezghani , Taicir Loukil, Belaid Aouni, (2011), MANAGER PREFERENCES MODELLING FOR STOCHASTIC AGGREGATE PLANNING, Multiple Criteria Decision Making (6), pp. 149-162

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Scopus citations in 2 paper(s):
  1. Jamalnia, A., Yang, J. -., Feili, A., Xu, D. -., & Jamali, G. (2019). Aggregate production planning under uncertainty: A comprehensive literature survey and future research directions. International Journal of Advanced Manufacturing Technology, 102(1-4), 159-181. doi:10.1007/s00170-018-3151-y
  2. Jamalnia, A., Yang, J. -., Xu, D. -., Feili, A., & Jamali, G. (2019). Evaluating the performance of aggregate production planning strategies under uncertainty in soft drink industry. Journal of Manufacturing Systems, 50, 146-162. doi:10.1016/j.jmsy.2018.12.009