A Research On Location Of A Three-level Supply Chain Oriented To Product Family

Location research is an important part of the supply chain management research,which is the primary task of enterprise’s strategic planning, and also will affect theperformance of the operation and management. Now, with the development ofeconomy and the general improvement of people’s living standard, the needs ofcustomers are no longer satisfied with the market products, more and more customersare pursuing individual and diversified products. In such a market environment,product life cycles are getting shorter, product variety is rapidly expanding, customers’demand for the service level is getting higher, which challenges the traditional supplychain.Most of the existing location studies focusing on single-product or multi-product,pay a little consideration to similarities among products and the influence of thesimilarities to supply chain performance. Product family, as a special case of themulti-product, if the similarity characteristics are convert to reuse, the supply chainwill have competitive advantages, such as reducing management cost and inventorycost, accelerate the response to market, which has its important practical and guidingsignificance to enhance the overall competitiveness of the supply chain. Therefore,based on a product family as the research object, this paper studies the locationproblem of supply chain.In order to achieve economy scale benefits of mass customization productionmode, this paper let the product family model that has been modularized andstandardized join the supply chain research. Under the random demand driven andcertain service level, let the common modules and customized module participate inthe activities of the supply chain, to minimize the sum of construction cost, inventorycost and transportation cost as the goal, we set up a nonlinear integer programmingmodel used to make location, inventory and distribution decisions.In the process of solving the model, based on Lagrangian relaxation algorithm,the lower bound and upper bound are obtained by decomposition method step by step,and by narrowing the gap between the lower bound and the upper bound, anapproximate optimal solution of this model is got, thus location selection, inventoryand distribution decisions are solved at the same time. At the end of the paper, a numerical example is given to prove the feasibility and effectiveness of the algorithm.