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On modeling stochastic dynamic vehicle routing problems
Journal article   Open access   Peer reviewed

On modeling stochastic dynamic vehicle routing problems

Marlin W. Ulmer, Justin C. Goodson, Dirk C. Mattfeld and Barrett W. Thomas
EURO Journal on Transportation and Logistics, Vol.9(2), pp.1-14
06/01/2020
DOI: 10.1016/j.ejtl.2020.100008
url
https://doi.org/10.1016/j.ejtl.2020.100008View
Published (Version of record) Open Access

Abstract

Operations research requires models that unambiguously define problems and support the generation and presentation of solution methodology. In the field of dynamic routing, capturing the joint evolution of complex sequential routing decisions and stochastic information is challenging, leading to a situation where rigorous methods have outpaced rigorous models and thus making it difficult for researchers to engage in rigorous science. We provide a modeling framework that strongly connects application with method and that leverages the rich body of route-based planning and optimization. As a generalization of conventional Markov decision processes (MDPs), route-based MDPs augment the state space, action space, and reward structure to include routing information. Accordingly, route-based MDPs make it conceptually easier to connect dynamic routing problems with the route-based methods typically used to solve them – construct and revise routes as new information is learned. We anticipate route-based MDPs will facilitate more scientific rigor in dynamic routing studies, provide researchers with a common modeling language, allow for better inquiry, and improve classification and description of solution methods. •We establish a theoretical basis for combining route-based optimization with dynamic and stochastic modeling.•We present a modeling framework based on routing plans, connecting the model to both the application and the solution method.•In contrast to existing SDVRP literature surveys, our review compares and contrasts modeling techniques and solution methods.•We demonstrate how route-based MDP formulations more closely align problem models with state-of-the-art solution approaches
 Literature review Markov decision process Modeling framework Stochastic dynamic vehicle routing

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