A Multimodal Location and Routing Model for Hazardous Materials Transportation based on Multi-commodity Flow Model

Jiang, Yang; Zhang, Xingchen; Ye, Rong; Zhang, Zheng

doi:10.1016/j.sbspro.2014.07.262

Cited by 28 publications

(10 citation statements)

References 12 publications

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“…(2012) × × × × × × Case study Boyer et al. (2013) × × × × × × Case study Samanlioglu (2013) × × × × × × Case study Berglund and Kwon (2014) × × × × × × × Numerical experiment Jiang et al. (2014) × × × × × × Case study Ardjmand et al.…”

Section: Literature Reviewmentioning

confidence: 99%

A stochastic network design problem for hazardous waste management

Sun

Solvang

et al. 2020

Journal of Cleaner Production

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Hazardous waste management is of paramount importance due to the potential threats posed to the environment and local residents. The design of a hazardous waste management system involves several important decisions, i.e., the determination of the locations and sizes of treatment, recycling and disposal facilities, and organizing the transportation of hazardous waste among different facilities. In this paper, we proposed a novel stochastic bi-objective mixed integer linear program (MILP) to support these decisions in order to reduce the population exposure to risk while simultaneously maintaining a high cost efficiency of the transportation and treatment of hazardous waste. Moreover, considering the inherent uncertainty within the planning horizon, the cost, demand and affected population are defined as stochastic parameters. A sample average approximation based goal programming (SAA-GP) approach is used to solve the mathematical model. The proposed model and solution method are validated through numerical experiments whose results show that uncertainty may not only affect the objective value but also lead to different strategic decisions in the network design of a hazardous waste management system. In this regard, the strategic decisions obtained by the stochastic model is more robust to the change of external environment. Finally, the model is applied in a real-world case study of healthcare waste management in Wuhan, China, in order to show its applicability.

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Section: Literature Reviewmentioning

confidence: 99%

A stochastic network design problem for hazardous waste management

Sun

Solvang

et al. 2020

Journal of Cleaner Production

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“…Xie et al [1] presented a representative study on the hazardous materials multimodal location-routing problem, in which a bi-objective nonlinear model is designed and a linear reformulation method is developed to solve the problem. Inspired by Xie et al's study [1], Jiang et al [31] explored the same problem based on a multicommodity flow model. Compared with the above two articles that only consider origins, destinations and volumes of the transportation orders of hazardous materials, an improvement on the above two articles was achieved by Verma and Verter [27].…”

Section: Literature Reviewmentioning

confidence: 99%

A Bi-Objective Fuzzy Credibilistic Chance-Constrained Programming Approach for the Hazardous Materials Road-Rail Multimodal Routing Problem under Uncertainty and Sustainability

Sun

Li²,

Liang

et al. 2019

Sustainability

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Hazardous materials transportation involves extensive risk and cannot be avoided in practice. An advanced routing, however, can help to reduce the risk by planning the best transportation routes for hazardous materials that can make effective tradeoffs between the risk objective and the economic objective. In this study, we explore the hazardous materials routing problem in the road-rail multimodal transportation network with a hub-and-spoke structure, in which the risk is measured by the multiplication of population exposure and the associated volume of hazardous materials, and minimizing the total risk of all the transportation orders of hazardous materials is set as the risk objective. It is difficult to estimate the population exposure exactly during the routing decision-making process, which results in its uncertainty. In this study, we formulate the uncertain population exposure from a fuzzy programming perspective by using triangular fuzzy numbers. Moreover, the carbon dioxide emission constraint is formulated to realize the sustainable transportation of hazardous materials. To optimize the problem under the above framework, we first establish a bi-objective fuzzy mixed integer nonlinear programming model, and then develop a three-stage exact solution strategy that the combines fuzzy credibilistic chance constraint, linearization technique, and the normalized weighting method. Finally, a computational experiment is carried out to verify the feasibility of the proposed method in dealing with the problem. The experimental results indicate that tradeoffs between the two conflicting objectives can be effectively made by using the Pareto frontier to the hazardous materials routing problem. Furthermore, the credibility level and carbon dioxide emission cap significantly influence the hazardous materials routing optimization. Their effects on the optimization result are quantified by using sensitivity analysis, which can draw some useful insights to help decision makers to better organize the hazardous materials road-rail multimodal transportation under uncertainty and sustainability.

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“…Several studies have combined it with real problems which can lead to this type of transport-specific characteristics of the case study addressed. In the last few years, many more applications of intermodal transport have become available, for instance: intermodal transportation of hazardous material (HAZMAT) in which we look for minimising transportation cost and the risk associated with the transportation of hazardous material (Jiang et al, 2014); wood transportation, freight activities of British intermodal rail (Woodburn, 2012); optimal links and locations for transportation hub in Marmara region (Resat & Turkay, 2015); intermodal rail study from Asia to Europe (Rodemann & Templar, 2014). The applications suggested in the fields of logistics are not exhaustive.…”

Section: Fig 1 Some Steps Of the Agricultural Supply Chainmentioning

confidence: 99%

Modelling and solving a bi-objective intermodal transport problem of agricultural products

Abbassi¹,

Alaoui²,

Boukachour³

2018

10.5267/j.ijiec

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During the past few years, transportation of agricultural products is increasingly becoming a crucial problem in supply chain logistics. In this paper, we present a new mathematical formulation and two solution approaches for an intermodal transportation problem. The proposed bi-objective model is applied to the transportation of agricultural products from Morocco to Europe to minimise both the transportation cost either in the form of uni-modal or intermodal, as well as the maximal overtime to delivery products. The first solution approach is based on a non-dominated sorting genetic algorithm improved by a local search heuristic and the second one is the GRASP algorithm (Greedy Randomised Adaptive Search Procedure) with iterated local search heuristics. They are tested on theoretical and real case benchmark instances and compared with the standard NSGA-II. Results are analysed and the efficiency of algorithms is discussed using some performance metrics.

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A Multimodal Location and Routing Model for Hazardous Materials Transportation based on Multi-commodity Flow Model

Cited by 28 publications

References 12 publications

A stochastic network design problem for hazardous waste management

A stochastic network design problem for hazardous waste management

A Bi-Objective Fuzzy Credibilistic Chance-Constrained Programming Approach for the Hazardous Materials Road-Rail Multimodal Routing Problem under Uncertainty and Sustainability

Modelling and solving a bi-objective intermodal transport problem of agricultural products

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