A Monotone Approximate Dynamic Programming Approach for the Stochastic Scheduling, Allocation, and Inventory Replenishment Problem: Applications to Drone and Electric Vehicle Battery Swap Stations

Amin Asadi () and Sarah Nurre Pinkley ()
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Amin Asadi: Department of Industrial Engineering and Business Information Systems, University of Twente, 7522 NB Enschede, Netherlands; Department of Industrial Engineering, University of Arkansas, Fayetteville, Arkansas 72701
Sarah Nurre Pinkley: Department of Industrial Engineering, University of Arkansas, Fayetteville, Arkansas 72701

Transportation Science, 2022, vol. 56, issue 4, 1085-1110

Abstract: There is a growing interest in using electric vehicles (EVs) and drones for many applications. However, battery-oriented issues, including range anxiety and battery degradation, impede adoption. Battery swap stations are one alternative to reduce these concerns that allow the swap of depleted for full batteries in minutes. We consider the problem of deriving actions at a battery swap station when explicitly considering the uncertain arrival of swap demand, battery degradation, and replacement. We model the operations at a battery swap station using a finite horizon Markov decision process model for the stochastic scheduling, allocation, and inventory replenishment problem (SAIRP), which determines when and how many batteries are charged, discharged, and replaced over time. We present theoretical proofs for the monotonicity of the value function and monotone structure of an optimal policy for special SAIRP cases. Because of the curses of dimensionality, we develop a new monotone approximate dynamic programming (ADP) method, which intelligently initializes a value function approximation using regression. In computational tests, we demonstrate the superior performance of the new regression-based monotone ADP method compared with exact methods and other monotone ADP methods. Furthermore, with the tests, we deduce policy insights for drone swap stations.

Keywords: electric vehicles and drones; battery swap station; Markov decision processes; battery degradation; monotone policy and value function; regression-based initialization; approximate dynamic programming (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:56:y:2022:i:4:p:1085-1110

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