Genetic Algorithm-Based Relocation Scheme in Electric Vehicle Sharing Systems

  • Junghoon Lee
  • Gyung-Leen Park
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 253)


This paper designs a genetic algorithm-based relocation scheme for electric vehicle sharing systems, which suffer from the stock imbalance problem due to different rent-out and return patterns in different stations. To improve the service ratio, the relocation scheme explicitly moves vehicles from overflow stations to underflow stations. Each relocation plan is encoded to an integer-valued vector, based on two indexes, one for the overflow list, and the other for the underflow list. In each list, stations are bound to specific locations according to the number of surplus or needed vehicles. For a vector element, its location is the overflow station index, while the value is the underflow index. Iterative genetic operations improve the population quality, computed by the relocation distance, generation by generation. The simulation result shows that the proposed relocation scheme finds an efficient relocation plan in the early stage of iterations for the given parameter set.


Smart transportation Electric vehicle sharing system Vehicle relocation Genetic algorithms Relocation distance 


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  1. 1.Department of Computer Sciences and StatisticsJeju National UniversityJejuRepublic of Korea

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