Service based logistics optimization
Author(s)Price, Gregory D., Jr
Leaders for Global Operations Program.
Deborah Nightingale and Dimitris Bertsimas.
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This thesis explores the use of a service based logistics optimization (SBLO) methodology for an inbound reverse logistics network. Currently, Quest Diagnostics solves the vehicle routing problem with time windows (VRPTW) in designing routes. The objective of the canonical VRPTW is to find a minimum cost route that visits every node once while meeting time window and capacity constraints without consideration to service levels. Since many of the nodes in Quest's logistics network receive multiple pickups per day, have time-sensitive biological specimens, and require different service levels, the SBLO is more aligned with service objectives. First, a spatio-temporal network model is created for every client in the logistics network. Next, a key service level metric (logistics turn-around-time) is defined. Finally, the SBLO is developed and tested on a small geographic area in Brighton, MA. The results of the two week pilot were promising; service levels improved 25%, labor costs per requisition decreased by 10%-15%, and additional capacity was created the 2nd and 3rd shifts. Although the effectiveness of the SBLO will be different for each route, the gains in service, reductions in cost, and increases in efficiency of the pilot warrant an investigation of the new optimization methodology applied to the entire logistics network. Quest could theoretically start processing 28% of the total New England testing volume by the 1st or 2nd shift, lowering operational costs, increasing efficiencies, and improving service levels dramatically. Additionally, this service based optimization strategy provides a value proposition that is more aligned with customer value expectations.
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT.Thesis: S.M., Massachusetts Institute of Technology, Engineering Systems Division, 2014. In conjunction with the Leaders for Global Operations Program at MIT.18Cataloged from PDF version of thesis.Includes bibliographical references (pages 109-110).
DepartmentSloan School of Management.; Massachusetts Institute of Technology. Engineering Systems Division.; Leaders for Global Operations Program.
Massachusetts Institute of Technology
Sloan School of Management., Engineering Systems Division., Leaders for Global Operations Program.