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

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...

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Veröffentlicht in:Operational research Jg. 18; H. 2; S. 497 - 519
1. Verfasser: Murakami, Keisuke
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2018
Springer Nature B.V
Schlagworte:
Algorithms
Business and Management
Computational Intelligence
Economic impact
Electric vehicles
Environmental impact
Hybrid electric vehicles
Integer programming
Management Science
Operations Research
Operations Research/Decision Theory
Original Paper
Production scheduling
Rechargeable batteries
Recharging
Route planning
Scheduling
Sockets
Routing and scheduling problem
Labeling algorithm
Plug-in hybrid electric vehicle
Mixed integer programming problem
ISSN:1109-2858, 1866-1505
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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
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ISSN:1109-2858
1866-1505
DOI:10.1007/s12351-016-0274-5