A two-phase optimization method for a multiobjective vehicle relocation problem in electric carsharing systems

A two-phase optimization method for a multiobjective vehicle relocation problem in electric... The paper focuses on one-way electric carsharing systems, where the fleet of cars is made up of Electric Vehicles (EVs) and the users can pick-up the EV at a station and return it to a different one. Such systems require efficient vehicle relocation for constantly balancing the availability of EVs among stations. In this work, the EVs are relocated by workers, and the issue of finding a trade-off among the customers’ satisfaction, the workers’ workload balance and the carsharing provider’s objective is addressed. This leads to a three-objective optimization problem for which a two-phase solution approach is proposed. In the first phase, feasible routes and schedules for relocating EVs are generated by different randomized search heuristics; in the second phase, non-dominated solutions are found through epsilon-constraint programming. Computational results are performed on benchmark instances and new large size instances based on the city of Milan. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Combinatorial Optimization Springer Journals

A two-phase optimization method for a multiobjective vehicle relocation problem in electric carsharing systems

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Mathematics; Combinatorics; Convex and Discrete Geometry; Mathematical Modeling and Industrial Mathematics; Theory of Computation; Optimization; Operations Research/Decision Theory
ISSN
1382-6905
eISSN
1573-2886
D.O.I.
10.1007/s10878-018-0295-5
Publisher site
See Article on Publisher Site

Abstract

The paper focuses on one-way electric carsharing systems, where the fleet of cars is made up of Electric Vehicles (EVs) and the users can pick-up the EV at a station and return it to a different one. Such systems require efficient vehicle relocation for constantly balancing the availability of EVs among stations. In this work, the EVs are relocated by workers, and the issue of finding a trade-off among the customers’ satisfaction, the workers’ workload balance and the carsharing provider’s objective is addressed. This leads to a three-objective optimization problem for which a two-phase solution approach is proposed. In the first phase, feasible routes and schedules for relocating EVs are generated by different randomized search heuristics; in the second phase, non-dominated solutions are found through epsilon-constraint programming. Computational results are performed on benchmark instances and new large size instances based on the city of Milan.

Journal

Journal of Combinatorial OptimizationSpringer Journals

Published: Apr 30, 2018

References

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