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Multicriteria Stochastic Shortest Path Problem for Electric Vehicles

Author

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  • Ehsan Jafari

    (The University of Texas at Austin)

  • Stephen D. Boyles

    (The University of Texas at Austin)

Abstract

This paper formulates the reliable routing of electric vehicles in stochastic networks as a multicriteria shortest path problem with travel time and charging cost components. The reliability term is defined as the probability of finishing the trip without running out of charge. The arc travel times are represented as stochastic variables, and arc energy consumption is modeled as a linear function of arc length and arc travel time. The traveler aims to minimize the generalized cost, formulated as a linear function of travel time and charging cost, subject to a minimum reliability threshold, representing the level of risk a traveler is willing to take in favor of routes with lower cost. We propose a solution algorithm based on generalized dynamic programming and show that the optimal solution may include cycles that visit at least one charging station. The properties of the proposed multicriteria shortest path problem are mathematically proved. The simulation results on randomly-generated networks show that cyclic paths are very rare, and that the generalized cost of travel is a monotone increasing function of minimum reliability threshold.

Suggested Citation

  • Ehsan Jafari & Stephen D. Boyles, 2017. "Multicriteria Stochastic Shortest Path Problem for Electric Vehicles," Networks and Spatial Economics, Springer, vol. 17(3), pages 1043-1070, September.
    • Handle: RePEc:kap:netspa:v:17:y:2017:i:3:d:10.1007_s11067-017-9358-x
    DOI: 10.1007/s11067-017-9358-x
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    References listed on IDEAS

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