Planning and design of intermodal hub networks: A literature review

Basallo-Triana, Mario José; Holguín, Carlos Julio Vidal; Bravo-Bastidas, Juan José

doi:10.1016/j.cor.2021.105469

Cited by 30 publications

(16 citation statements)

References 120 publications

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“…The transport process itself also requires the appropriate type of vehicle to be used in order to make the most rational use of the above-mentioned infrastructure elements (Facca et al, 2021). Loading units used in intermodal transport are inseparable from the type of vehicle and, depending on the volume of freight transported, have a direct impact on the efficiency of intermodal transport (Basallo-Triana et al, 2021).…”

Section: Criteriamentioning

confidence: 99%

Factors influencing intermodal transport efficiency and sustainability

Filina-Dawidowicz¹,

Stankiewicz²,

Čižiūnienė³

et al. 2022

CogSust

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A dynamic development of intermodal transport is observed worldwide. This development, among other issues, is related to increasing the level of transport efficiency and sustainability. That increase presents a challenge for the participants of intermodal transport systems. Therefore, there is a need to analyze the factors influencing the efficiency and sustainability of intermodal transport. The article aims to analyze these factors considering the viewpoint of transport chains participants. Ten factors influencing intermodal transport efficiency and sustainability were identified. The case study of Polish market was analyzed using marketing research tool. The questionary was developed, and the survey was carried out among the representatives of intermodal terminals located at seaports, rail-road terminals and forwarders. On the basis of collected information, it was possible to set the ranking of the particular factors. It was stated that efficient handling of cargo and transport means in transshipment terminals forms the most important factor from the practitioners’ viewpoint.

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Section: Criteriamentioning

confidence: 99%

Factors influencing intermodal transport efficiency and sustainability

Filina-Dawidowicz¹,

Stankiewicz²,

Čižiūnienė³

et al. 2022

CogSust

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“…The design of intermodal HLPs is reviewed in [10], where most of the 100 works that are considered were published between 2014 and 2020. Most of those works are static deterministic MILP models, very few are multiperiod ones, and the literature dealing with uncertainty is very scarce, mainly devoted to dealing with disruptive events at the hubs and the links.…”

Section: Static Deterministic Hub Locationmentioning

confidence: 99%

“…Constraint (9) defines the step character of the η-binary variables. It also prevents additional capacity modules expansion in a strategic node n (i.e., η n kq = 1), in case the related hub was not made available in any of its ancestor nodes (i.e., γ (10) prevents the capacity module expansion at any hub in a strategic node in case the hub has not previously been made available in an ancestor node. Note that the constraint system ( 9) and (10) prevents the same number of additional capacity modules to be expanded in a hub in any successor to node n, where η n kq − η…”

Section: Dem For Ms-hub-nepmentioning

confidence: 99%

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On Multistage Multiscale Stochastic Capacitated Multiple Allocation Hub Network Expansion Planning

Escudero

Monge

2021

Mathematics

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The hub location problem (HLP) basically consists of selecting nodes from a network to act as hubs to be used for flow traffic directioning, i.e., flow collection from some origin nodes, probably transfer it to other hubs, and distributing it to destination nodes. A potential expansion on the hub building and capacitated modules increasing along a time horizon is also considered. So, uncertainty is inherent to the problem. Two types of time scaling are dealt with; specifically, a long one (viz., semesters, years), where the strategic decisions are made, and another whose timing is much shorter for the operational decisions. Thus, two types of uncertain parameters are also considered; namely, strategic and operational ones. This work focuses on the development of a stochastic mixed integer linear optimization modeling framework and a matheuristic approach for solving the multistage multiscale allocation hub location network expansion planning problem under uncertainty. Given the intrinsic difficulty of the problem and the huge dimensions of the instances (due to the network size of realistic instances as well as the cardinality of the strategic scenario tree and operational ones), it is unrealistic to seek an optimal solution. A matheuristic algorithm, so-called SFR3, is introduced, which stands for scenario variables fixing and iteratively randomizing the relaxation reduction of the constraints and variables’ integrality. It obtains a (hopefully, good) feasible solution in reasonable time and a lower bound of the optimal solution value to assess the solution quality. The performance of the overall approach is computationally assessed by using stochastic-based perturbed well-known CAB data.

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“…However, understanding these structures is inherently more difficult due to their dynamic complexity [17], the evolution of the network [18], the diversity of connections [19] or the diversity of nodes. There is little research to enhance the properties of the ports and their links [20]. With the rapid development of the global economy, commodity characteristics and environmental factors will also affect shipping decisions [21].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Container Shipping Network Reconfiguration under RCEP

Zhao

2022

JMSE

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Due to its advantages of large transportation volume and low transportation cost, container shipping has become an important transportation mode in current international trade. The recovery of the shipping industry in 2021 and the signing of RCEP make the reconfiguration and optimization of the container shipping network a very important task at present. The network service capability is an important factor affecting the container shipping network. Based on the complex network theory, the coefficients of port location, the importance of distance and route among ports are taken as the service capacity reconfiguration coefficients of the global container shipping network. A max-min mixed integer model is established for global container shipping network reconfiguration. A sort of communication-reducing conjugate gradient method based on Krylov Subspace (CR-CG-KS) is proposed to reduce the reconfiguration computation. The results show that the global container shipping network does not need large-scale reconfiguration but requires small-scale changes to optimize the network feature vector centrality and make the network more balanced and stable. This study is beneficial for business managers to proactively respond to the future development of the shipping network and improve the operational efficiency of the global container shipping network.

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Planning and design of intermodal hub networks: A literature review

Cited by 30 publications

References 120 publications

Factors influencing intermodal transport efficiency and sustainability

Factors influencing intermodal transport efficiency and sustainability

On Multistage Multiscale Stochastic Capacitated Multiple Allocation Hub Network Expansion Planning

Optimization of Container Shipping Network Reconfiguration under RCEP

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