In Vehicle Sharing Systems (VSSs), users can rent a vehicle paying a charge depending only on the actual time of use. In one-way VSSs, they are also allowed to delivery a vehicle to a station that may be different from the one of pick-up. This of course introduces flexibility but also poses the problem of re-balancing the demand and the supply of vehicles between the stations by means of operators. We address the Electric Vehicles Relocation Problem (EVReP) assuming that the operators directly drive vehicles (indeed cars in our application) from a station of pick-up to one of delivery, moving by folding bicycles from a station of delivery to one of pick-up, as in Bruglieri et al. (2014) and Bruglieri et al. (2017). Collaboration among operators is also possible through the ”carpooling”, i.e., an operator can give a lift to the others moving from a station of pick-up to one of delivery. We study the economic sustainability of the collaborative EVReP through a Mixed Integer Linear Programming (MILP) formulation assuming that a revenue is associated with each relocation request satisfied and an hourly cost with the operators used. The MILP allows routing and scheduling the operators with the objective of maximizing the total profit, i.e., the difference between the total satisfied request revenue and the total operator cost. The constraints allow satisfying the requests within their time windows and taking into account the limited EV battery autonomy. Through numerical experiments on real like instances, we show that the collaboration among operators can improve the total profit of the carsharing system. Moreover, the new MILP formulation outperforms the previous ones also in terms of computational time being based on two-indices variables by elimination of their dependency on the relocation operators.

The Collaborative Relocation in One-Way Electric Carsharing Systems / Bruglieri, Maurizio; Marinelli, Fabrizio; Pisacane, Ornella. - ELETTRONICO. - (2019), pp. 178-178. (Intervento presentato al convegno International Conference on Optimization and Decision Science (ODS2019) tenutosi a Dept. of Economics and Business Studies (Università di Genova) nel 4-7 September 2019).

The Collaborative Relocation in One-Way Electric Carsharing Systems

Fabrizio Marinelli;Ornella Pisacane
2019-01-01

Abstract

In Vehicle Sharing Systems (VSSs), users can rent a vehicle paying a charge depending only on the actual time of use. In one-way VSSs, they are also allowed to delivery a vehicle to a station that may be different from the one of pick-up. This of course introduces flexibility but also poses the problem of re-balancing the demand and the supply of vehicles between the stations by means of operators. We address the Electric Vehicles Relocation Problem (EVReP) assuming that the operators directly drive vehicles (indeed cars in our application) from a station of pick-up to one of delivery, moving by folding bicycles from a station of delivery to one of pick-up, as in Bruglieri et al. (2014) and Bruglieri et al. (2017). Collaboration among operators is also possible through the ”carpooling”, i.e., an operator can give a lift to the others moving from a station of pick-up to one of delivery. We study the economic sustainability of the collaborative EVReP through a Mixed Integer Linear Programming (MILP) formulation assuming that a revenue is associated with each relocation request satisfied and an hourly cost with the operators used. The MILP allows routing and scheduling the operators with the objective of maximizing the total profit, i.e., the difference between the total satisfied request revenue and the total operator cost. The constraints allow satisfying the requests within their time windows and taking into account the limited EV battery autonomy. Through numerical experiments on real like instances, we show that the collaboration among operators can improve the total profit of the carsharing system. Moreover, the new MILP formulation outperforms the previous ones also in terms of computational time being based on two-indices variables by elimination of their dependency on the relocation operators.
2019
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/269540
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