BUS606: Operations and Supply Chain Management

This study proposed a multi-objective, multi-commodity distribution planning model that integrates location and inventory control decisions in a multi-echelon supply chain network with multiple capacity centres in a stochastic environment. An interactive stochastic goal programming formulation for food production is developed. The goal of the model is to select the optimum numbers, locations, and capacity levels of the warehouses to deliver the products to the retailers at the least cost, while satisfying the desired service level. The modelling approach of this model is distinguished from the other models in this field by the fact that DMs' imprecise aspiration levels for the goals, and retailers' imprecise demand are incorporated into the model using a stochastic modelling approach, which is otherwise not possible by conventional mathematical programming methods.

This paper also contributes to the literature by proposing a novel and generic SGP-based solution approach that determines the preferred compromise solution for multi-objective decision problems.

An Iranian food industry case study was used to demonstrate the feasibility of the proposed method for real distribution problems. Some realistic scenarios have been investigated, based on the DMs' strategies. These strategies can be compared by determining the performance vector for each strategy. The proposed method yields an efficient solution and overall degree of DMs' satisfaction with the determined objective values. Accordingly, the proposed method is practically applicable to solving real-world multi-objective DPD problems in an uncertain environment.