Coordinated Location, Distribution, and Inventory Decisions in Supply Chain Network Design
Read this article. The goal is to understand optimum product allocation and distribution locations so products are delivered at the lowest possible cost. As you read Part 2, what are some other problems associated with supply chain allocation and distribution?
Summary and Conclusion
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.