Novel decision model based on mixed chase and level strategy for aggregate production planning under uncertainty: Case study in beverage industry. (December 2017)

• Record Type: Journal Article
• Authors: Jamalnia, Aboozar; Yang, Jian-Bo; Xu, Dong-Ling; Feili, Ardalan
• Is Part Of: Computers & industrial engineering. Volume 114(2017)
• Page Start: 54
• Page End: 68
• Publication Date: 2017-12
• Subjects: Aggregate production planning (APP) -- Uncertainty -- Stochastic nonlinear multi-objective optimisation; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2017.09.044
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: A decision model is proposed to aggregate production planning under uncertainty. The proposed multiple objective model is based on mixed chase and level strategy. The model is validated using real world data from beverage manufacturing industry. The wait and see approach is applied to solve the constructed decision model. Sensitivity analysis and several forms of trade-off analysis are also conducted. Abstract: The present study proposes a novel decision model to aggregate production planning (APP) decision making problem based on mixed chase and level strategy under uncertainty where the market demand acts as the main source of uncertainty. By taking into account the novel features, the constructed model turns out to be stochastic, nonlinear, multi-stage and multi-objective. APP in practice entails multiple-objectivity. Therefore, the model involves multiple objectives such as total revenue, total production costs, total labour productivity costs, optimum utilisation of production resources and capacity and customer satisfaction, and is validated on the basis of real world data from beverage manufacturing industry. Applying the recourse approach in stochastic programming leads to empty feasible space, and therefore the wait and see approach is used instead. After solving the model using the real-world industrial data, sensitivity analysis and several forms of trade-off analysis are conducted by changing different parameters/coefficients of the constructed model, and by analysing the compromise between objectives respectively. Finally, possible future research directions, with regard to the limitations of current study, are discussed.