Possibilistic Mixed Integer Linear Programming Approach for Production Allocation and Distribution Supply Chain Network Problem in the Consumer Goods Industry

In the consumer goods industry there is an ongoing trend towards an increased product variety and shorter replenishment cycle times. Hence, manufacturers seek a better coordination of production and distribution activities. Our study is motivated by the production-distribution problem encountered by a soft-drink company operating in consumer goods industry. The problem is to determine the optimal allocation of products and routing decisions for a multi-echelon supply chain to minimize the total supply chain cost comprising of production, setup, inventory and distribution costs. A mixed integer linear programming (MILP) model is proposed to describe the optimization problem. However, a real supply chain operates in a highly dynamic and uncertain environment. The ambiguity of cost parameters is considered in the objective function of the model. The proposed approach uses the strategy of minimizing the most possible cost, maximizing the possibility of obtaining lower cost, and minimizing the risk of obtaining higher cost. Zimmermann's fuzzy multi objective programming method is then applied for achieving an overall satisfactory compromise solution. The applicability of the proposed model is illustrated through a case study in consumer goods industry

Supply chain network modeling in a golf club industry via fuzzy linear programming approach

This paper addresses a supply chain network planning problem faced by a company that manages a golf club supply chain. The supply chain network is considered for the production of several products through an assembly of three modules supplied by different suppliers. A linear programming model is proposed to describe the problem, where multiple components can be assembled within a planning horizon of one to twelve months. The model involves the supply of various components from a set of suppliers and allocation of assembled products to customers. In real world problems practical situations are often not well-defined and thus can not be described precisely. Therefore this model is transformed into the fuzzy models with flexibility in the objective function, in the market demand, and in the available capacity of resources. The main objective is to construct a procurement-assembly plan enabling it to minimize its costs while satisfying the customers' demand over a given planning horizon in such a way as to hedge against uncertainty. Finally, the proposed model is tested using a case of supply chain from the golf club industry. Sensitivity analyses are also conducted on various parameters to gain insight into the proposed model. Numerical case demonstrates that the proposed fuzzy model can provide a better and more flexible way of representing the problem for the considered industry