Design of a reliable multi-modal multi-commodity model for hazardous materials transportation under uncertainty

Mohammadi, Mehrdad; Jula, Payman; Tavakkoli–Moghaddam, Reza

doi:10.1016/j.ejor.2016.07.054

Cited by 71 publications

(29 citation statements)

References 64 publications

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“…that corresponds to Cr n ≥ a { }. Accordingly, equation (23) can be reformulated as equations (28) and (29). Equation (24) can be directly converted into equations (30) and (31):…”

Section: Defuzzification Of the Fuzzy Constraintsmentioning

confidence: 99%

“…e objective functions of this model are equations (22) and (5). Its constraint set contains equations (6) to (12) and 14, equations (18) to (20), and equations (28) to (31). Among these equations, equations (11), (14), and (16) are nonlinear constraints and equation 22is a nonlinear objective.…”

Section: Defuzzification Of the Fuzzy Constraintsmentioning

confidence: 99%

“…Finally, this study can obtain a single-objective mixed integer linear programming model for the road-rail intermodal routing problem investigated by this study. Such a model consists of equation (43) as the objective and equations (6) to (10), equations (18) to (20), equations (28) to (37), and equations (39) to (42) as the constraints. Since the model is linear and yields only one optimization objective, it can be solved by the exact solution algorithm implemented by the mathematical programming software.…”

Section: Weighted Sum Approachmentioning

confidence: 99%

“…In the road-rail intermodal routing problem, reliability means the successful accomplishment of transportation orders by using planned road-rail intermodal routes [26]. Uncertainty is the primary factor that influences the reliability of intermodal transportation [27][28][29]. Although a short-term planning [8], the routing optimization should be undertaken before the actual transportation starts [30].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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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“…that corresponds to Cr n ≥ a { }. Accordingly, equation (23) can be reformulated as equations (28) and (29). Equation (24) can be directly converted into equations (30) and (31):…”

Section: Defuzzification Of the Fuzzy Constraintsmentioning

confidence: 99%

Section: Defuzzification Of the Fuzzy Constraintsmentioning

confidence: 99%

Section: Weighted Sum Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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“…Similarly, an improved multi-commodity network flow (MCNF) model was introduced to holistically assess a multi modal transportation system and to identify the optimal flows achievable [15]. Taking uncertainty scenarios into consideration, a reliable multi-modal multi-commodity model was made by Mohammadi et al [16]. Taslimi et al designed a comprehensive modelling framework for HAZMAT transport network design, HAZMAT response team location and equity of risk [1].…”

Section: Introductionmentioning

confidence: 99%

Routing for Hazardous Materials Transportation in Urban Areas

Zhang

Feng

Yan³

et al. 2019

Symmetry

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Hazardous materials (HAZMAT) are important for daily production in cities, which usually have a high population. To avoid the threat to public safety and security, the routes for HAZMAT transportation should be planned legitimately by mitigating the maximum risk to population centers. For the objective of min-max local risk in urban areas, this study has newly proposed an optimization model where the service of a link for HAZMAT transportation was taken as the key decision variable. Correspondingly, the symmetric problem of min-max optimization takes significant meanings. Moreover, in consideration of the work load of solving the model under a lot of decision variables, a heuristic algorithm was developed to obtain an optimal solution. Thereafter, a case study was made to test the proposed model and algorithm, and the results were compared with those generated by deterministic solving approaches. In addition, this research is able to be an effective reference for authorities on the management of HAZMAT transportation in urban areas.

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Managing rail-truck intermodal transportation for hazardous materials with random yard disruptions

2020

Ann Oper Res

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Design of a reliable multi-modal multi-commodity model for hazardous materials transportation under uncertainty

Cited by 71 publications

References 64 publications

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

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

Routing for Hazardous Materials Transportation in Urban Areas

Managing rail-truck intermodal transportation for hazardous materials with random yard disruptions

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