Application of Fuzzy mathematical programming approach to the aggregate production/distribution planning in a supply chain network problem

Abstract

This paper presented an application of Fuzzy mathematical programming model to solve network design problems for supply chains via considering aggregate production planning (APP). APP goals to minimize all costs through optimal levels of production, subcontracting, inventory, backorder and work levels over a time period to meet the demand. Fuzzy logic was applied to solve the uncertain production/distribution/subcontracting costs and capacities. However, most of the existing models deal the APP problems without integrating supply chain networks. In our model, APP and supply chain design problem were considered within a single plan horizon to get better managerial results. A supply chain network which includes suppliers, manufacturers, subcontracts, retailers and customers, was developed to illustrate the performance of the proposed model. A numerical example was presented to clarify the features proposed approach. In applying the model, decision makers should find a potential to represent their human resources policies regarding the overtime and subcontract production under material requirements constraints. Key words: Supply chain network optimization, aggregate production planning, material requirements constraint, triangular Fuzzy numbers, possibilistic linear programming.