Rollout Policies for Dynamic Solutions to the Multivehicle Routing Problem with Stochastic Demand and Duration Limits

Justin C. Goodson (), Jeffrey W. Ohlmann () and Barrett W. Thomas ()
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Justin C. Goodson: Department of Operations and Information Technology Management, John Cook School of Business, Saint Louis University, St. Louis, Missouri 63108
Jeffrey W. Ohlmann: Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242
Barrett W. Thomas: Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242

Operations Research, 2013, vol. 61, issue 1, 138-154

Abstract: We develop a family of rollout policies based on fixed routes to obtain dynamic solutions to the vehicle routing problem with stochastic demand and duration limits (VRPSDL). In addition to a traditional one-step rollout policy, we leverage the notions of the pre- and post-decision state to distinguish two additional rollout variants. We tailor our rollout policies by developing a dynamic decomposition scheme that achieves high quality solutions to large problem instances with reasonable computational effort. Computational experiments demonstrate that our rollout policies improve upon the performance of a rolling horizon procedure and commonly employed fixed-route policies, with improvement over the latter being more substantial.

Keywords: rollout policy; approximate dynamic programming; stochastic vehicle routing; fixed routes (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (36)

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