Robust Strategic Route Planning in Logistics

Logistics is a cost sensitive industry with large and fast growing routing networks. In this paper the authors devise a computational, robust optimization method for the strategic routing decisions of a logistics’ customer, i.e., a company that uses the services of different freight forwarders to meet its transportation demands between several sources, sinks, and hubs. The costs of such transports are determined by tariff systems that typically show economies of scale and reward the consolidation of goods that complement each other in properties relevant for transport, such as weight and volume. In the strategic planning phase, routes and hubs have to be chosen roughly one year ahead, in particular, before the actual demand is known. The authors' method anticipates the fluctuation of demands by minimizing the worst-case cost over a restricted scenario set. The combination of a realistic cost function, a robust modeling of uncertainty, and large-scale networks leads to highly intractable models. The authors show that the corresponding adversary problem is non-deterministic polynomial-time (NP)-hard. To nevertheless find solutions for real instances with very good worst-case cost the authors derive a carefully relaxed and simplified mixed-integer linear program that solves well for large instances because of its powerful linear programming relaxation. The authors test the method for real-world instances. The results show that robust optimization can significantly reduce worst-case cost. Furthermore, the authors derive from their method two heuristic techniques to solve even larger networks and report on the corresponding computational results. Neglecting the typical uncertainty about demand values can cause significant cost in logistic routing problems. This paper provides for a practical method to avoid such costs.

• Record URL:
  • https://doi.org/10.1287/trsc.2016.0683
• Record URL:
  • https://pubsonline.informs.org/doi/abs/10.1287/trsc.2016.0683
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/1767714
• Supplemental Notes:
  • Abstracts reprinted with permission of INFORMS (Institute for Operations Research and the Management Sciences, http://www.informs.org).
• Authors:
  • Richter, Alexander T
  • Stiller, Sebastian
• Publication Date: 2018-1

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 38-58
• Serial:
  • Transportation Science
  • Volume: 52
  • Issue Number: 1
  • Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
  • ISSN: 0041-1655
  • Serial URL: http://transci.journal.informs.org/

Subject/Index Terms

• TRT Terms: Costs; Customers; Freight forwarders; Logistics; Mixed integer programming; Optimization; Route choice; Strategic planning
• Subject Areas: Freight Transportation; Operations and Traffic Management; Planning and Forecasting;

Filing Info

• Accession Number: 01664195
• Record Type: Publication
• Files: TRIS
• Created Date: Mar 26 2018 9:20AM