The paper reports the results of a research targeted to develop a Decision Support System (DSS) for planning and operation of urban deliveries carried out with electric vans. The research was included within the 2019-21 Research Program for the Electric System, coordinated by the Italian Ministry for the Ecological Transition, and has been performed by ENEA, the Italian Agency for Energy, New Technologies and Sustainable Development, and “La Sapienza” University of Rome. The new DSS is based on meta-heuristics algorithms capable to manage a generic set of goods to be delivered by means of a generic fleet of electric vans, with the objective of minimizing the overall cost of the daily operation. The algorithm considers all the physical constraints, including vehicles batteries capacity. It is assumed that fast recharges can be performed during the delivery tours. For the real-time operation, a monitoring system of the vehicle fleet, road network and recharge stations is assumed, based on IoT technologies, in order to detect possible unexpected events and manage them in the best way, according to the available resources time by time. The paper describes the DSS general architecture, the optimization algorithms and the recovery procedures and shows results for two testbeds
A platform to optimize urban deliveries with e-vans
Maria Pia Valentini
;Valentina Conti;Matteo Corazza;Maria Lelli;Silvia Orchi;Fernando Ortenzi;Giuseppe Tomasino;
2023-01-01
Abstract
The paper reports the results of a research targeted to develop a Decision Support System (DSS) for planning and operation of urban deliveries carried out with electric vans. The research was included within the 2019-21 Research Program for the Electric System, coordinated by the Italian Ministry for the Ecological Transition, and has been performed by ENEA, the Italian Agency for Energy, New Technologies and Sustainable Development, and “La Sapienza” University of Rome. The new DSS is based on meta-heuristics algorithms capable to manage a generic set of goods to be delivered by means of a generic fleet of electric vans, with the objective of minimizing the overall cost of the daily operation. The algorithm considers all the physical constraints, including vehicles batteries capacity. It is assumed that fast recharges can be performed during the delivery tours. For the real-time operation, a monitoring system of the vehicle fleet, road network and recharge stations is assumed, based on IoT technologies, in order to detect possible unexpected events and manage them in the best way, according to the available resources time by time. The paper describes the DSS general architecture, the optimization algorithms and the recovery procedures and shows results for two testbedsFile | Dimensione | Formato | |
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