Restocking-Based Rollout Policies for the Vehicle Routing Problem with Stochastic Demand and Duration Limits

Justin C. Goodson (), Barrett W. Thomas () and Jeffrey W. Ohlmann ()
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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
Barrett W. Thomas: Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242
Jeffrey W. Ohlmann: Department of Management Sciences, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242

Transportation Science, 2016, vol. 50, issue 2, 591-607

Abstract: We develop restocking-based rollout policies to make real-time, dynamic routing decisions for the vehicle routing problem with stochastic demand and duration limits . Leveraging dominance results, we develop a computationally tractable method to estimate the value of an optimal restocking policy along a fixed route. Embedding our procedure in rollout algorithms, we show restocking-based rollout outperforms a priori-based rollout, demonstrating the value of explicitly considering preemptive capacity replenishment in a rollout approach for dynamic routing. We also demonstrate the effectiveness of basic local search versus more sophisticated mechanisms for the heuristic component of the rollout procedure.

Keywords: stochastic vehicle routing; rollout policies; dynamic programming (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:50:y:2016:i:2:p:591-607

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