Intermodal transport in freight distribution: a literature review

Agamez-Arias, Anny-del-Mar; Fuentes, José Moyano

doi:10.1080/01441647.2017.1297868

Cited by 91 publications

(49 citation statements)

References 99 publications

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“…The routes can be optimized according to different criteria. Traditionally, the optimization models concentrate on costs or time [32]. However, various surveys show that multiple criteria, among others also sustainability and reliability, are important for transportation planners [33,34].…”

Section: Literature Reviewmentioning

confidence: 99%

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A Time‐Dependent Fuzzy Programming Approach for the Green Multimodal Routing Problem with Rail Service Capacity Uncertainty and Road Traffic Congestion

et al. 2018

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This study explores an operational-level container routing problem in the road-rail multimodal service network. In response to the demand for an environmentally friendly transportation, we extend the problem into a green version by using both emission charging method and bi-objective optimization to optimize the CO2 emissions in the routing. Two uncertain factors, including capacity uncertainty of rail services and travel time uncertainty of road services, are formulated in order to improve the reliability of the routes. By using the triangular fuzzy numbers and time-dependent travel time to separately model the capacity uncertainty and travel time uncertainty, we establish a fuzzy chance-constrained mixed integer nonlinear programming model. A linearization-based exact solution strategy is designed, so that the problem can be effectively solved by any exact solution algorithm on any mathematical programming software. An empirical case is presented to demonstrate the feasibility of the proposed methods. In the case discussion, sensitivity analysis and bi-objective optimization analysis are used to find that the bi-objective optimization method is more effective than the emission charging method in lowering the CO2 emissions for the given case. Then, we combine sensitivity analysis and fuzzy simulation to identify the best confidence value in the fuzzy chance constraint. All the discussion will help decision makers to better organize the green multimodal transportation.

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Section: Literature Reviewmentioning

confidence: 99%

“…Define a 0-1 variable φ Step The arrival time of the containers of a transportation order at the origin equals its earliest release time. Eq.9 (32), (33), and (34) where g k is a newly introduced variable.…”

Section: Crisp Equivalent and Linearization Of The Fuzzy Chancementioning

confidence: 99%

A Time‐Dependent Fuzzy Programming Approach for the Green Multimodal Routing Problem with Rail Service Capacity Uncertainty and Road Traffic Congestion

et al. 2018

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“…Low-carbon logistics is conducive to energy conservation and footprint reduction for logistics companies, improving market competitiveness [3] and building a sustainable economic system with low-carbon manufacturing and consumption. Compared with single road transportation, multimodal transportation can effectively reduce transportation costs by 20% [4] and CO 2 footprint by 57% [5] and is an effective and sustainable transportation method. In 2016, the Paris Agreement put forward energy conservation and carbon footprint reduction targets: "By 2020, China's unit gross domestic product CO 2 footprint will fall by 40% to 45%; by 2030 it will fall by 60% to 65%."…”

Section: Introductionmentioning

confidence: 99%

Synergy Degree Evaluation of Container Multimodal Transport System

Fang

Zhi-ya

et al. 2020

Sustainability

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Logistics activities are an important source of energy consumption and environmental issues. Research conclusions and practical experience show that promoting the development of container multimodal transport is an effective way to reduce the level of carbon footprint. The key to influencing the development of container multimodal transport lies in the cooperation of all participants and links (modes of transport, transport businesses). Evaluating the synergy degree is a key step in this development process. This paper takes the whole process of container multimodal transportation as the research perspective, analyzes the operation process, and treats the process as a production system composed of four subsystems: facilities and equipment, organizational management, business operations, and information interactions. Through in-depth interviews and an analysis of the academic literature and policy documents, we establish a synergy degree evaluation index system and measurement model of container multimodal transport based on synergy theory and case studies. The research results are consistent with the actual situation. From 2015 to 2018, the synergy of container multimodal transport system of China's G port developed slowly, but generally moved in a more orderly direction.Sustainability 2020, 12, 1487 2 of 26 of cargo transportation; by 2020, the volume of port railway collection and distribution and container multimodal transport will increase significantly. Multimodal container operation is an important economic activity and plays a vital role in transportation and low-carbon development.In actual operation, logistics companies tend to choose a single mode of transport when conditions permit. The reason is that the participants and links (modes of transport, transport businesses) are not coordinated, due to the following: (1) There is a lack of effective connection between infrastructures. For example, many ports have no dedicated railway lines, which greatly increases transportation costs.(2) There is no uniform standard for equipment. The size standards of road trucks are different from the standards of railway loading units, and the conversion is very troublesome, requiring loading and unloading, resulting in increased costs. (3) The devices are not completely intelligent. The development of special railway wagons, railway dual-use trailers, and river-sea combined carriers is lagging, and the connection efficiency is low. (4) There is a lack of multimodal transport integration service providers. Due to the lack of a large logistics network platform and effective deployment, small transportation companies are blind, and there is often repeated transportation and wasting of resources. (5) Information docking and sharing are difficult. There is no uniform information exchange standard and format between enterprises, and each enterprise is an information island. In addition, there is a lack of effective connection between multiple modes of transport, and the costs of short barges, reloading, loading and unloading...

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“…This study investigates a collaborative intermodal transportation network considering the corridor choice and vehicle arrangements simultaneously. A unit cost function is first developed to capture the characteristics of the economics of scale in the collaborative intermodal freight transport network, relevant researches refer to Christiansen et al [13]; Bektas and Crainic [14]; Caris et al [15]; M. SteadieSeif [16] and Anny-del-Mar [17]. Considering the economics of scale, Kimms [18] and Racunica and Wynter [18] present an optimization model that addresses the problem of economies of scale brought about by freight consolidation through using a hub-and-spoke network.…”

Section: Introductionmentioning

confidence: 99%

Design and Freight Corridor-Fleet Size Choice in Collaborative Intermodal Transportation Network Considering Economies of Scale

et al. 2019

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Decentralized freight decision has been proved to be one of the inhibitors to achieve a sustainable transport network. One important method also a key challenge is to determine how to coordinate and consolidate the transportation flow to get the best logistics performance. This study presents an intermodal transportation network considering freight consolidation through freight forwarders’ cooperation. We formulate the problem as a minimum intermodal transport cost model, which is a nonlinear, nonconvex and discontinuous function that involves volume economies of scale, distance economies of scale and vehicle size economies of scale. A hybrid genetic algorithm (GA) and particle swarm optimization (PSO) algorithm in combination with a batch strategy are used to solve the problem. Five different transport demand scenarios are tested on a real case on “China Railway Express” (Crexpress). The choices of reasonably corridor and fleet size combination are provided.

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Intermodal transport in freight distribution: a literature review

Cited by 91 publications

References 99 publications

A Time‐Dependent Fuzzy Programming Approach for the Green Multimodal Routing Problem with Rail Service Capacity Uncertainty and Road Traffic Congestion

A Time‐Dependent Fuzzy Programming Approach for the Green Multimodal Routing Problem with Rail Service Capacity Uncertainty and Road Traffic Congestion

Synergy Degree Evaluation of Container Multimodal Transport System

Design and Freight Corridor-Fleet Size Choice in Collaborative Intermodal Transportation Network Considering Economies of Scale

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