Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Kaveh Khalili-Damghani, Ayda Shahrokh, Alireza Pakgohar

Abstract

In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.


Keywords

Uncertain aggregate production planning; Supply chain management; Automotive Industry

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