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Journal of Combinatorial Optimization

Erschienen in:

30.04.2018

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

verfasst von: Maurizio Bruglieri, Ferdinando Pezzella, Ornella Pisacane

Erschienen in: Journal of Combinatorial Optimization | Ausgabe 1/2018

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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.

Vorheriger Artikel Asymptotically optimal policy for stochastic job shop scheduling problem to minimize makespan

Nächster Artikel New lower bounds for the second variable Zagreb index

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Titel: A two-phase optimization method for a multiobjective vehicle relocation problem in electric carsharing systems
verfasst von: Maurizio Bruglieri
Ferdinando Pezzella
Ornella Pisacane
Publikationsdatum: 30.04.2018
Verlag: Springer US
Erschienen in: Journal of Combinatorial Optimization / Ausgabe 1/2018
Print ISSN: 1382-6905
Elektronische ISSN: 1573-2886
DOI: https://doi.org/10.1007/s10878-018-0295-5

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