This article presents two methods for solving the electric vehicles (EVs) relocation in EV-sharing system: 1) a centralized method where the decisions are taken by a unique decision-maker by using the complete knowledge of the system and 2) a randomized matheuristic algorithm where decisions are taken by the stations that coordinate for solving the relocation problem. For each methodology, two approaches are proposed for the EV relocation, i.e., the relocation performed by the EV-sharing operators and the relocation involving registered users also with an incentive scheme based on the crowdsourcing concept. In both the methods, two integer linear programming (ILP) problems are formulated to minimize the relocation cost in the two considered approaches. Moreover, in the randomized matheuristic method, a set of smart stations solve local ILP problems to produce a relocation plan. Finally, some instances and a case study are presented to demonstrate the effectiveness of the proposed approaches for the EVs relocation problem.

Innovative Approaches for Electric Vehicles Relocation in Sharing Systems / Fanti, Maria Pia; Mangini, Agostino Marcello; Roccotelli, Michele; Silvestri, Bartolomeo. - In: IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING. - ISSN 1545-5955. - STAMPA. - 19:1(2022), pp. 21-36. [10.1109/TASE.2021.3103808]

Innovative Approaches for Electric Vehicles Relocation in Sharing Systems

Maria Pia Fanti;Agostino Marcello Mangini;Michele Roccotelli;Bartolomeo Silvestri
2022-01-01

Abstract

This article presents two methods for solving the electric vehicles (EVs) relocation in EV-sharing system: 1) a centralized method where the decisions are taken by a unique decision-maker by using the complete knowledge of the system and 2) a randomized matheuristic algorithm where decisions are taken by the stations that coordinate for solving the relocation problem. For each methodology, two approaches are proposed for the EV relocation, i.e., the relocation performed by the EV-sharing operators and the relocation involving registered users also with an incentive scheme based on the crowdsourcing concept. In both the methods, two integer linear programming (ILP) problems are formulated to minimize the relocation cost in the two considered approaches. Moreover, in the randomized matheuristic method, a set of smart stations solve local ILP problems to produce a relocation plan. Finally, some instances and a case study are presented to demonstrate the effectiveness of the proposed approaches for the EVs relocation problem.
2022
Innovative Approaches for Electric Vehicles Relocation in Sharing Systems / Fanti, Maria Pia; Mangini, Agostino Marcello; Roccotelli, Michele; Silvestri, Bartolomeo. - In: IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING. - ISSN 1545-5955. - STAMPA. - 19:1(2022), pp. 21-36. [10.1109/TASE.2021.3103808]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/228342
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