The Stochastic Vehicle Routing Problem for Minimum Unmet Demand

Zhihong Shen (), Fernando Ordòñez () and Maged M. Dessouky ()
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Zhihong Shen: University of Southern California
Fernando Ordòñez: University of Southern California
Maged M. Dessouky: University of Southern California

A chapter in Optimization and Logistics Challenges in the Enterprise, 2009, pp 349-371 from Springer

Abstract: Summary In this chapter, we are interested in routing vehicles to minimize unmet demand with uncertain demand and travel time parameters. Such a problem arises in situations with large demand or tight deadlines so that routes that satisfy all demand points are difficult or impossible to obtain. An important application is the distribution of medical supplies to respond to large-scale emergencies, such as natural disasters or terrorist attacks. We present a chance constrained formulation of the problem that is equivalent to a deterministic problem with modified demand and travel time parameters under mild assumptions on the distribution of stochastic parameters and relate it to a robust optimization approach. A tabu heuristic is proposed to solve this MIP and simulations are conducted to evaluate the quality of routes generated from both deterministic and chance constrained formulations. We observe that chance constrained routes can reduce the unmet demand by around 2%-6% for moderately tight deadline and total supply constraints.

Keywords: Tabu Search; Vehicle Rout Problem; Demand Point; Demand Node; Unmet Demand (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1007/978-0-387-88617-6_13

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