Bridging the gap between weak-demand areas and public transport using an ant-colony simulation-based optimization

Calabrò, Giovanni; Inturri, Giuseppe; Pira, Michela Le; Pluchino, Alessandro; Ignaccolo, Matteo

doi:10.1016/j.trpro.2020.03.012

Cited by 26 publications

(10 citation statements)

References 16 publications

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“…In general, ACO is conceived to find the minimum cost paths within a network, so it presents several applications to routing and scheduling problems and is of particular interest in transport problems [4,17]. Besides, thanks to its easy applicability to dynamic problems, where the topology of the characteristics of the network changes during the simulation, ACO algorithms are able to perform better than other metaheuristics.…”

Section: The Use Of Ant Colony Optimization To Solve the Vrpmentioning

confidence: 99%

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Calabrò

Torrisi

Inturri

et al. 2020

Eur. Transp. Res. Rev.

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This paper presents the first results of an agent-based model aimed at solving a Capacitated Vehicle Routing Problem (CVRP) for inbound logistics using a novel Ant Colony Optimization (ACO) algorithm, developed and implemented in the NetLogo multi-agent modelling environment. The proposed methodology has been applied to the case study of a freight transport and logistics company in South Italy in order to find an optimal set of routes able to transport palletized fruit and vegetables from different farms to the main depot, while minimizing the total distance travelled by trucks. Different scenarios have been analysed and compared with real data provided by the company, by using a set of key performance indicators including the load factor and the number of vehicles used. First results highlight the validity of the method to reduce cost and scheduling and provide useful suggestions for large-size operations of a freight transport service.

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Section: The Use Of Ant Colony Optimization To Solve the Vrpmentioning

confidence: 99%

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Calabrò

Torrisi

Inturri

et al. 2020

Eur. Transp. Res. Rev.

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“…e results showed that DRT shared services are convenient under specific demand patterns for the analysed case studies. Based on these studies, Calabrò et al [44] presented an ABM tailored to solve the last-mile problem of MRT in lowdemand areas, identifying optimal routes of feeder services.…”

Section: Literature Reviewmentioning

confidence: 99%

Fixed-Route vs. Demand-Responsive Transport Feeder Services: An Exploratory Study Using an Agent-Based Model

Calabrò

Pira

Giuffrida

et al. 2022

Journal of Advanced Transportation

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Feeder transport services are fundamental as first and last-mile connectors of mass rapid transit (MRT). They are especially beneficial in low-demand areas where private transport is usually the main transport mode. Besides, the rapid spread of new technologies such as vehicle automation and the shared mobility paradigm gave rise to new mobility-on-demand modes that can dynamically match demand with service supply. In this context, the new generation of real-time demand-responsive transport services can act as on-demand feeders of MRT, but their performance needs to be compared with conventional fixed-route fixed-schedule feeders. This article aims at presenting an agent-based model able to simulate different feeder services and explore the conditions that make a demand-responsive feeder (DRF) service more or less attractive than a fixed-route fixed-schedule feeder (FRF). The parametric simulation environment creates realistic constraints and parameters that are usually not included in analytical models because of high computational complexity. First, we identified the critical demand density representing a switching point between the two services. Once the demand density is fixed, exploratory scenarios are tested by changing the demand spatial distribution and patterns, service area, and service configurations. Main results suggest that the DRF is to be preferred when the demand is spatially concentrated close to the MRT station (e.g., in a TOD-like land-use area) or when station spacing is quite high (e.g., a regional railway service), whereas the FRF performs better when the demand is mainly originated at the MRT station to any other destinations in the service area (e.g., during peak hours). Besides, automated vehicles could play a role in reducing the operator cost if the service is performed with many small vehicles rather than higher-capacity vehicles, even if this would not imply a major benefit gain for the users.

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“…The ABM approach allows for a more realistic and natural transition to the overall performance evaluation of the system by describing the behaviour of microscopic subjects and the interactions between them [15]. Nourinejad and Roorda showed the positive role of dynamic ride-sharing in terms of user cost and vehicle kilometre travelled (VKT) savings by designing centralized (binary integer programming) and decentralized (dynamic auction-based multiagent) optimization algorithms to match passengers and drivers [16].…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation-Based Modelling of the Impact of Ridesharing on Urban System

Sun¹,

Liu²,

Zhang³

et al. 2022

Int. j. simul. model.

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This paper follows the basic principles of taxi dynamics and uses an agent-based modelling approach (ABM) to simulate the underlying road network, vehicles and passenger situations in an urban environment and to carry out evaluations. First, based on two evaluation metrics: passenger travel time and total number of passengers transported, a comparison is made between the ride-hailing system (RH) and the system with ridesharing under different supply and demand rates, revealing the impact of ridesharing on system efficiency at urban scale. Then, in the ridesharing system (RS), four levels of supply are taken as examples, and passenger travel time is disaggregated to quantify how the definition of vicinity in the matching process affects the passenger travel time, passenger waiting time and vehicle detour time in a given city. Finally, a summary of the level of supply and the range of vicinity where ridesharing can be effective is presented in terms of the total distance travelled by the system. From a city management perspective, these results can help in the analysis and planning of efficient transport services.

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Bridging the gap between weak-demand areas and public transport using an ant-colony simulation-based optimization

Cited by 26 publications

References 16 publications

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Improving inbound logistic planning for large-scale real-world routing problems: a novel ant-colony simulation-based optimization

Fixed-Route vs. Demand-Responsive Transport Feeder Services: An Exploratory Study Using an Agent-Based Model

Simulation-Based Modelling of the Impact of Ridesharing on Urban System

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