Integrated Logistics Network Design and Inventory

Management in Service Parts Logistics

 

Mehmet Candas

Operations Research and Industrial Engineering Graduate Program

Department of Mechanical Engineering

The University of Texas at Austin

 

We study the integrated logistics network design and inventory stocking problem as characterized by the interdependency of the design and stocking decisions in service parts logistics. These two sets of decisions have been usually considered sequentially in practice, and the associated problems have been tackled separately in the research literature. The overall problem is typically further complicated due to time-based service constraints that provide lower limits for the percentages of demand satisfied within specified time windows.  We introduce an optimization model that explicitly captures the interdependency between network design (locating facilities, and allocating customers to facilities) and inventory stocking decisions (stock levels and their corresponding stochastic fill rates). We have computational results from our extensive experiments showing that the integrated approach can provide significant cost savings over the disintegrated approaches.  Further, we analyze a special case of the general problem, where each customer requires a certain time-based service level. We show that this case has polynomially solvable subcases, but in general it is still a challenging problem, for which we have a Lagrangian-relaxation based approach that provides extremely tight lower and upper bounds.

 

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