An integrated location and routing approach for transporting hazardous materials in a bi-modal transportation network

Ghaderi, Abdolsalam; Burdett, Robert L.

doi:10.1016/j.tre.2019.04.011

Cited by 89 publications

(36 citation statements)

References 29 publications

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“…Lowering costs reflects the customer demand on improving transportation economy and is always the most important objective of intermodal routing optimization. Even in the multi-objective optimization on the intermodal routing problem, for example, the hazardous materials routing problem [29,30] and fresh food routing problem [31], the economic objective plays an important role in the optimization. A few studies on the intermodal routing problem, e.g., Chang [8] and Moccia et al [32], adopt a piecewise linear cost function that shows the effect of economies of scale to calculate the economic objective.…”

Section: Review On Modeling Customer Demand On Economy In the Intermomentioning

confidence: 99%

Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncertainty

Sun

Li²

2019

Mathematics

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In this study, we systematically investigate a road-rail intermodal routing problem the optimization of which is oriented on the customer demands on transportation economy, timeliness and reliability. The road-rail intermodal transportation system is modelled as a hub-and-spoke network that contains time-flexible container truck services and scheduled container train services. The transportation timeliness is optimized by using fuzzy soft time windows associated with the service level of the transportation. Reliability is enhanced by considering multiple sources of time uncertainty, including road travel time and loading/unloading time. Such uncertainty is modelled by using fuzzy set theory. Triangular fuzzy numbers are adopted to represent the uncertain time. Under the above consideration, we first establish a fuzzy mixed integer nonlinear programming model with a weighted objective that includes minimizing the costs and maximizing the service level for accomplishing transportation orders. Then we use the fuzzy expected value model and fuzzy chance-constrained programming separately to realize the defuzzification of the fuzzy objective and use fuzzy chance-constrained programming to deal with the fuzzy constraint. After defuzzification and linearization, an equivalent mixed integer linear programming (MILP) model is generated to enable the problem to be solved by mathematical programming software. Finally, a numerical case modified from our previous study is presented to demonstrate the feasibility of the proposed fuzzy programming approaches. Sensitivity analysis and fuzzy simulation are comprehensively utilized to discuss the effects of the fuzzy soft time windows and time uncertainty on the routing optimization and help decision makers to better design a crisp transportation plan that can effectively make tradeoffs among economy, timeliness and reliability.

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Section: Review On Modeling Customer Demand On Economy In the Intermomentioning

confidence: 99%

Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncertainty

Sun

Li²

2019

Mathematics

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“…Considering the self-duality property of the fuzzy credibility measure, this study utilizes fuzzy credibilistic chanceconstrained programming to take care of the fuzzy constraints. e fuzzy credibilistic chance constraints of equations (16) and (17) are as following equations (23) and (24), respectively, where Cr{ } is the credibility that a fuzzy event in { } happens and λ ∈ [0, 1.0] is the credibility level that is set subjectively by decision makers based on their preference:…”

Section: Defuzzification Of the Fuzzy Constraintsmentioning

confidence: 99%

“…It aims at the selection of the best routes to move containers of transportation orders demanded by customers from origins to destinations through the road-rail intermodal transportation network [11]. e best routes can either achieve optimum on any one of the objectives, e.g., minimal cost [3,12,13], minimal time [14,15], lowest risk [16,17], and minimal greenhouse gas emissions [18], or make tradeoffs among them in multiobjective optimizations.…”

Section: Introductionmentioning

confidence: 99%

Green and Reliable Freight Routing Problem in the Road-Rail Intermodal Transportation Network with Uncertain Parameters: A Fuzzy Goal Programming Approach

Sun

2020

Journal of Advanced Transportation

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In this study, the author focuses on modeling and optimizing a freight routing problem in a road-rail intermodal transportation network that combines the hub-and-spoke and point-to-point structures. The operations of road transportation are time flexible, while rail transportation has fixed departure times. The reliability of the routing is improved by modeling the uncertainty of the road-rail intermodal transportation network. Parameters that are influenced by the real-time status of the network, including capacities, travel times, loading and unloading times, and container trains’ fixed departure times, are considered uncertain in the routing decision-making. Based on fuzzy set theory, triangular fuzzy numbers are employed to formulate the uncertain parameters as well as resulting uncertain variables. Green routing is also discussed by treating the minimization of carbon dioxide emissions as an objective. First of all, a multiobjective fuzzy mixed integer nonlinear programming model is established for the specific reliable and green routing problem. Then, defuzzification, linearization, and weighted sum method are implemented to present a crisp linear model whose global optimum solutions can be effectively obtained by the exact solution algorithm run by mathematical programming software. Finally, a numerical case is given to demonstrate how the proposed methods work. In the case, sensitivity analysis is adopted to reveal the effects of uncertainty on the routing optimization. Fuzzy simulation is then performed to help decision makers to select the best crisp route plan by determining the best confidence level shown in the fuzzy chance constraints.

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“…In the uncertain environment, the multiobjective path probability-constrained model and the multiobjective path probability-dependent model for hazardous material transportation were proposed. Ghaderi and Robert [23] proposed an integrated location and routing approach for transporting hazardous materials in a bimodal transportation network. López-Ramos et al [24] presented an integrated model and specialized local search for the road network pricing and the design of hazmat vehicles.…”

Section: Introductionmentioning

confidence: 99%

Design of a Network Optimization Platform for the Multivehicle Transportation of Hazardous Materials

Dong

Zhou

2020

IJERPH

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With economic development, the volume of hazardous materials is increasing, and the potential risks to human beings and the natural environment are expanding. Road transportation has become the main mode of transportation for hazardous materials. Because of the specific characteristics of hazardous materials, if an accident occurs in the transportation process, it often causes mass casualties, serious property and socioeconomic damage, and damage to the ecological environment. Hence, transportation is an important part of the life cycle of hazardous materials. This paper designs an optimization platform for multidestination, multiterminal, and multivehicle networks that transport hazardous materials. The logistics module in TransCAD software is used to construct this platform. By identifying the effective transportation routes considering the transportation risk, sensitive target population, and transportation time of each road section, the entropy method can be used to fuse and obtain the comprehensive impedance value of each road section. Finally, the optimal transportation network of hazardous materials was obtained by the transportation network optimization algorithm in TransCAD. The platform can display the optimal transport program with data windows, text, and maps. The research results provide a reference for relevant departments to scientifically manage the transport of hazardous materials.

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An integrated location and routing approach for transporting hazardous materials in a bi-modal transportation network

Cited by 89 publications

References 29 publications

Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncertainty

Fuzzy Programming Approaches for Modeling a Customer-Centred Freight Routing Problem in the Road-Rail Intermodal Hub-and-Spoke Network with Fuzzy Soft Time Windows and Multiple Sources of Time Uncertainty

Green and Reliable Freight Routing Problem in the Road-Rail Intermodal Transportation Network with Uncertain Parameters: A Fuzzy Goal Programming Approach

Design of a Network Optimization Platform for the Multivehicle Transportation of Hazardous Materials

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