Pareto frontier analyses based decision making tool for transportation of hazardous waste

Das, Arup; Mazumder, Taraknath; Gupta, Anil K.

doi:10.1016/j.jhazmat.2012.05.068

Cited by 32 publications

(14 citation statements)

References 39 publications

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“…In the operational level, large numbers of studies focus on the vehicle routing problem (VRP) for the hazardous materials transportation, e.g., Bula et al [12], Du et al [13], Ma et al [14], and Kheirkhah et al [15]. In these studies, the traditional VRP models are modified into a hazardous materials transportation scenario in which a risk objective is formulated to minimize the transportation risk and a bi-objective optimization is carried out to make tradeoffs between the economic objective and risk objective by using the Pareto frontier analysis [16]. Moreover, the vehicle location-routing problem (LRP) for the hazardous wastes transportation also draws some attention, e.g., Ardjmand et al [17], Zhao et al [18], Asgari et al [19] and Alumur and Kara [20].…”

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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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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“…Finally, a case study was conducted. Das et al [14] studied the transportation route problem of hazardous waste in a transportation network with capacity constraints. Using a multiobjective algorithm, they solved the network transportation problem with multiple destinations and terminals and found the nondominated solutions.…”

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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“…Xie and Travis Waller proposed advanced labeling algorithm to solve the double-objective transportation route optimization model with single origin destination point [ 18 ]. Das et al examined the transportation route problem of transportation network with limited capacity, and found non-dominated solutions from the multi-objective algorithm for multiple starting and end points transportation network [ 19 – 20 ]. Ma et al analyzed the transportation route choice problem under certain and uncertain environments, and proposed the multi-objective route planning model of certain environment, multi-objective route chance constrained model, and multi-objective route opportunities dependent model of uncertain environment [ 21 – 23 ].…”

Section: Introductionmentioning

confidence: 99%

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm

Hao

Pan

et al. 2018

PLoS ONE

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Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg–Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

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Pareto frontier analyses based decision making tool for transportation of hazardous waste

Cited by 32 publications

References 39 publications

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

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

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

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm

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