The concept of innovation in transport systems requires the satisfaction of two main objectives: flexibility and costs minimization. The demand responsive transport systems (DRTS) seem to be the solution for the trade-off between flexibility and efficiency. They require the planning of travel paths (routing) and customers pick-up and drop-off times (scheduling) according to received requests and respecting the limited capacity of the fleet and time constraints (hard time windows) for each networks node. Even considering invariable conditions of the network a DRTS may operate according to a static or to a dynamic mode. In the dynamic mode, customers requests arrive when the service is already running and, consequently, the solution may change over time. In this work, we use an algorithm able to solve a dynamic multi-vehicle DaRP by managing incoming transport demand as fast as possible. The heuristics is a greedy method that tries to assign the requests to one of the fleets vehicles finding each time the local optimum. The usage of vehicles only when strictly necessary, provides to costs minimization. The work is enriched by a series of tests with different values of the fleets vehicles and their capacity, of time windows and of incoming requests number. The solutions provided by the heuristics are simulated in a discrete events environment in which its possible to reproduce the movement of the buses, the passengers' arrival to the stops, and in the next step the delays due to the traffic congestion and possible anomalies in the behaviour of the passengers. Finally, at the end of the simulation, a set of performance indicators evaluate the solution planned by the heuristics.

Dynamic simulation of a flexible transport system

Pasquale Carotenuto;
2012

Abstract

The concept of innovation in transport systems requires the satisfaction of two main objectives: flexibility and costs minimization. The demand responsive transport systems (DRTS) seem to be the solution for the trade-off between flexibility and efficiency. They require the planning of travel paths (routing) and customers pick-up and drop-off times (scheduling) according to received requests and respecting the limited capacity of the fleet and time constraints (hard time windows) for each networks node. Even considering invariable conditions of the network a DRTS may operate according to a static or to a dynamic mode. In the dynamic mode, customers requests arrive when the service is already running and, consequently, the solution may change over time. In this work, we use an algorithm able to solve a dynamic multi-vehicle DaRP by managing incoming transport demand as fast as possible. The heuristics is a greedy method that tries to assign the requests to one of the fleets vehicles finding each time the local optimum. The usage of vehicles only when strictly necessary, provides to costs minimization. The work is enriched by a series of tests with different values of the fleets vehicles and their capacity, of time windows and of incoming requests number. The solutions provided by the heuristics are simulated in a discrete events environment in which its possible to reproduce the movement of the buses, the passengers' arrival to the stops, and in the next step the delays due to the traffic congestion and possible anomalies in the behaviour of the passengers. Finally, at the end of the simulation, a set of performance indicators evaluate the solution planned by the heuristics.
2012
Istituto Applicazioni del Calcolo ''Mauro Picone''
Inglese
Information Control Problems in Manufacturing
INCOM 2012 - 14th IFAC Symposium on Information Control Problems in Manufacturing
315
315
6
978-3-902661-98-2
http://www.ifac-papersonline.net/Detailed/53603.html
Sì, ma tipo non specificato
May 23-25, 2012
Bucharest (Romania)
Discrete-event Simulation; Modelling for Cooperative Transportation Systems; Heuristic and Metaheuristics
3
none
Baldassarre, Marco; Carotenuto, Pasquale; Raponi, Giuseppe
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/234185
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