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Comparing Static and Dynamic Policies for Vehicle Routing Problems with Backhauling and Dynamic Customer Demands

Comparing Static and Dynamic Policies for Vehicle Routing Problems with Backhauling and Dynamic Customer Demands

Subrata Mitra
Copyright: © 2013 |Volume: 4 |Issue: 2 |Pages: 17
ISSN: 1947-9573|EISSN: 1947-9581|EISBN13: 9781466633001|DOI: 10.4018/jal.2013040101
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MLA

Mitra, Subrata. "Comparing Static and Dynamic Policies for Vehicle Routing Problems with Backhauling and Dynamic Customer Demands." IJAL vol.4, no.2 2013: pp.1-17. http://doi.org/10.4018/jal.2013040101

APA

Mitra, S. (2013). Comparing Static and Dynamic Policies for Vehicle Routing Problems with Backhauling and Dynamic Customer Demands. International Journal of Applied Logistics (IJAL), 4(2), 1-17. http://doi.org/10.4018/jal.2013040101

Chicago

Mitra, Subrata. "Comparing Static and Dynamic Policies for Vehicle Routing Problems with Backhauling and Dynamic Customer Demands," International Journal of Applied Logistics (IJAL) 4, no.2: 1-17. http://doi.org/10.4018/jal.2013040101

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Abstract

Dynamic vehicle routing problems with backhauling (VRPB), although important, have attracted little attention in the literature. Dynamic VRPB is more complex than dynamic vehicle routing problems (VRP) without backhauling, and since VRP without backhauling is a special case of VRPB, models and algorithms for dynamic VRPB can easily be adapted for dynamic VRP. In this paper, the author compared between static and dynamic policies for solving VRPB with dynamic occurrences of customer delivery and pickup demands. They developed heuristic algorithms for medium-sized problems under static and dynamic policies. Although dynamic policies are always at least as good as static policies, the author observed from numerical experimentations that static policies perform relatively well for low degrees of dynamism (dod). On the other hand, dynamic policies are expected to perform significantly better than static policies for high dod and early availabilities of dynamic customer delivery and pickup demand information. The author concludes the paper by providing directions for future research on dynamic VRPB.

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