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Erschienen in:
2017 | OriginalPaper | Buchkapitel
4. Modeling
verfasst von : Marlin Wolf Ulmer
Erschienen in: Approximate Dynamic Programming for Dynamic Vehicle Routing
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Abstract
In this chapter, we model vehicle routing problems containing uncertainty and requiring stepwise planning by a (finite) Markov decision process (MDP). We define the MDP in Sect. 4.2. The MDP contains three (sub-)models: decision states, dynamic decision making, and stochastic transitions. To model routing applications as MDP, we have to determine the three (sub-)models. In Sect. 4.1, we model replanning as dynamism. In Sect. 4.4, we model a decision state for a vehicle routing’s planning situation. We model uncertainty as stochasticity. We give a short overview on how the main drivers of uncertainty generally are modeled in the literature in Sect. 4.5. We finally give an overview on how SDVRPs are modeled as MDPs in Sect. 4.6.