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Formulation and algorithms for route planning problem of plug-in hybrid electric vehicles

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  • Keisuke Murakami

    (Kansai University)

Abstract

Electric vehicles have recently received increasing attention because of their positive environmental and economic impacts; however, such vehicles are still not gaining widespread popularity for practical use given the inconvenience of limited battery capacity and long recharge times. To compensate for these drawbacks, plug-in hybrid electric vehicles (PHEVs) have been proposed, which can be recharged using standard household plug-in sockets unlike normal hybrid vehicles. Thus, PHEVs can run for long distances using widely available electrical power. Scheduling routes for the efficient use of electrical power is essential for PHEVs to succeed. Therefore, in this paper, we consider the PHEV routing and scheduling problem. We first formulate this problem as a mixed-integer programming (MIP) problem. Next, we propose three algorithms using a labeling method for large-scale problems; an exact algorithm and two heuristic algorithms. Our computational experiments show that the routes obtained using our algorithms are cost-efficient; further, our heuristic algorithms are much faster than the MIP formulation.

Suggested Citation

  • Keisuke Murakami, 2018. "Formulation and algorithms for route planning problem of plug-in hybrid electric vehicles," Operational Research, Springer, vol. 18(2), pages 497-519, July.
    • Handle: RePEc:spr:operea:v:18:y:2018:i:2:d:10.1007_s12351-016-0274-5
    DOI: 10.1007/s12351-016-0274-5
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    References listed on IDEAS

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    1. Ramteen Sioshansi, 2012. "OR Forum---Modeling the Impacts of Electricity Tariffs on Plug-In Hybrid Electric Vehicle Charging, Costs, and Emissions," Operations Research, INFORMS, vol. 60(3), pages 506-516, June.
    2. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    3. Schneider, M. & Stenger, A. & Goeke, D., 2014. "The Electric Vehicle Routing Problem with Time Windows and Recharging Stations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62382, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Arslan, Okan & Yıldız, Barış & Karaşan, Oya Ekin, 2015. "Minimum cost path problem for Plug-in Hybrid Electric Vehicles," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 80(C), pages 123-141.
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    Cited by:

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    2. Moritz Baum & Julian Dibbelt & Andreas Gemsa & Dorothea Wagner & Tobias Zündorf, 2019. "Shortest Feasible Paths with Charging Stops for Battery Electric Vehicles," Transportation Science, INFORMS, vol. 53(6), pages 1627-1655, November.
    3. Khalid Mekamcha & Mehdi Souier & Hakim Nadhir Bessenouci & Mohammed Bennekrouf, 2021. "Two metaheuristics approaches for solving the traveling salesman problem: an Algerian waste collection case," Operational Research, Springer, vol. 21(3), pages 1641-1661, September.

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