An intermodal optimum path algorithm for multimodal networks with dynamic arc travel times and switching delays

Ziliaskopoulos, Athanasios; Wardell, Whitney

doi:10.1016/s0377-2217(99)00388-4

Cited by 177 publications

(101 citation statements)

References 7 publications

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“…The trips based on the static schedule data may make planned transfers infeasible if some transit vehicles are late. In the multimodal routing context, many works have studied the multimodal shortest viable path problem [5], [6]. Three main problems are considered: (1) the set of transit modes used to accomplish the desired path; (2) the number of modal transfers performed in the desired path; and (3) the computational time to find the best solution in real time.…”

Section: Multimodal Journey Plannersmentioning

confidence: 99%

Distributed Multimodal Journey Planner Based on Mashup of Individual Planners’ APIs

Ferreira

Andrade

Ramos

et al. 2017

Communications in Computer and Information Science

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Section: Multimodal Journey Plannersmentioning

confidence: 99%

Distributed Multimodal Journey Planner Based on Mashup of Individual Planners’ APIs

Ferreira

Andrade

Ramos

et al. 2017

Communications in Computer and Information Science

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“…What type of disturbances must be prevented and how must containers be re-planned in case of a disturbance? Not many models for the routing of containers in intermodal networks are available (Ziliaskopoulos and Wardell, 2000, Macharis and Bontekoning, 2004, Cho et al, 2010. Most existing approaches consider the routing of containers as a part of the more general network design problem.…”

Section: Planning Of Container Network Transportationmentioning

confidence: 99%

“…Boardman et al (1997) used a method that selects the cheapest path per container on a real-time basis. Ziliaskopoulos (2000) proposed a model that selects the leasttime path, considering dynamic travel and transfer times. Cho et al (2010) used a weighted constrained shortest path problem to minimise time and cost for transports between two network nodes.…”

Section: Literature Reviewmentioning

confidence: 99%

Impact and relevance of transit disturbances on planning in intermodal container networks using disturbance cost analysis

et al. 2014

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An intermodal container transportation network is being developed between Rotterdam and several inland terminals in North West Europe: the EUROPEAN GATEWAY SERVICES network. This network is developed and operated by the sea terminals of EUROPE CONTAINER TERMINALS (ECT). To use this network cost-efficiently, centralised planning by the sea terminal of the container transportation is required. For adequate planning it is important to adapt to occurring disturbances. In this paper, a new mathematical model is proposed: the Linear Container Allocation model with Time-restrictions (LCAT). This model is used for determining the influence of three main types of transit disturbances on the network performance: early departure, late departure, and cancellation of inland services. The influence of a disturbance is measured in two ways. The impact measures the additional cost incurred by an updated planning in case of a disturbance. The relevance measures the cost difference between a fully updated and a locally updated plan. With the results of the analysis, key service properties of disturbed services that result in a high impact or high relevance can be determined. Based on this, the network operator can select focus areas to prevent disturbances with high impact and to improve the planning updates in case of disturbances with high relevance. In a case study of the EGS network, the impact and relevance of transit disturbances on all network services are assessed.

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“…The literature contains a number of approaches to intermodal freight planning (e.g., Caramia and Guerriero, 2009;Ziliaskopoulos and Wardell, 2000;Chang, 2008;Jansen et al, 2004). However, none of them applies to our problem since either (1) they do not handle all complicating factors that we need to consider, or (2) the combination of timetabled and demand driven transports are handled in an unsatisfactory way, e.g., by representing a demand driven transport as multiple timetabled departures, i.e., one for each time period.…”

Section: Transport Buyermentioning

confidence: 99%

TAPAS: A multi-agent-based model for simulation of transport chains

Holmgren

Davidsson

Persson

et al. 2012

Simulation Modelling Practice and Theory

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We present the Transportation And Production Agent-based Simulator (TAPAS), which is an agent-based model for simulation of transport chains that can be used, e.g., for analysis of transport-related policy and infrastructure measures. TAPAS is more powerful than traditional approaches to freight transport analysis, as it explicitly models production and customer demand, and it captures the interaction between individual transport chain actors, their heterogeneity and decision making processes, as well as time aspects. Whereas traditional approaches rely on assumed statistical correlation, TAPAS relies on causality, i.e., the focus is on the decisions and negotiations that lead to activities. TAPAS is composed of two connected layers, one that simulates the physical activities, e.g., production and transportation, and one that simulates the decision making and interaction between actors. We illustrate TAPAS with a scenario in which the consequences of three transport policy and infrastructure measures are studied.

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An intermodal optimum path algorithm for multimodal networks with dynamic arc travel times and switching delays

Cited by 177 publications

References 7 publications

Distributed Multimodal Journey Planner Based on Mashup of Individual Planners’ APIs

Distributed Multimodal Journey Planner Based on Mashup of Individual Planners’ APIs

Impact and relevance of transit disturbances on planning in intermodal container networks using disturbance cost analysis

TAPAS: A multi-agent-based model for simulation of transport chains

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