Routing hazardous materials on time-dependent networks using conditional value-at-risk

Toumazis, Iakovos; Kwon, Changhyun

doi:10.1016/j.trc.2013.09.006

Cited by 90 publications

(49 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is likely due to the greater importance and effectiveness of route selection on risk mitigation of supply chain networks. They are typically formulated as optimization problem where the minimization of cost, risk, or both objectives and risk equity constraints in hazmat transportation networks (Carotenuto et al 2007;Toumazis and Kwon 2013;Kang et al 2014b) are considered. Sometimes, intermodal routes are taken into consideration in the optimization model in order to satisfy customer delivery times (Verma and Verter 2010;Verma et al 2012).…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

2015

View full text Add to dashboard Cite

This paper illustrates a dynamic model of conditional value-at-risk (CVaR) measure for risk assessment and mitigation of hazardous material transportation in supply chain networks. The well-established market risk measure, CVaR, which is commonly used by financial institutions for portfolio optimizations, is investigated. In contrast to previous works, we consider CVaR as the main objective in the optimization of hazardous material (hazmat) transportation network. In addition to CVaR minimization and route planning of a supply chain network, the time scheduling of hazmat shipments is imposed and considered in the present study. Pertaining to the general dynamic risk model, we analyzed several scenarios involving a variety of hazmats and time schedules with respect to optimal route selection and CVaR minimization. A solution algorithm is then proposed for solving the model, with verifications made using numerical examples and sensitivity analysis.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

“…If the number of hazmat accidents on link (i, j) ∈ A l is assumed to follow a Poisson distribution with parameter μ i j , then the expected accident probability is estimated based on 1 μ i j . In this numerical analysis, the formulation given by Toumazis and Kwon (2013) is used for the estimation of μ i j :…”

Section: Network Informationmentioning

confidence: 99%

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

2015

View full text Add to dashboard Cite

show abstract

“…CVaR was first used in the financial sector to optimize portfolio [5]. Based on the good nature of CVaR used in a financial portfolio, Kwon et al [6] mainly studied the application of VaR and CVaR in hazmat transport, assume the probability of risk occurrence and consequences as a function of time. The above literatures laid a solid foundation to the study of CVaR optimization in hazmat transport.…”

Section: Reviewsmentioning

confidence: 99%

“…For a certain origin-destination (OD)pair, there are many connecting paths l L  , each path l consists of many segments l j A  , the consequences of risk occurrence is ij C and the corresponding probability of risk-happening is p ij ; The conditional value at risk can be expressed as (6). ij x indicates whether choose a path for transport.…”

Section: Model Of Single Transportation Mode Of Hazmat Based On Cvarmentioning

confidence: 99%

Routing Hazmat Multimodal Transportation Based on CVaR Assessment

Liu¹,

Du²,

Li³

et al. 2017

dtetr

View full text Add to dashboard Cite

Multimodal plays a more significant role in long distances transportation of hazardous materials, while there haven't been systemic risk evaluation methods to hazmat multimodal transportation. Considering that the risk of hazmat transportation has the characteristics of low probability and high consequence, this paper studies how CVaR applied to the routing optimization of hazmat multimodal transportation while CVaR could better compute the tail loss of risk. We build a multimodal hazmat transportation risk assessment model in this paper, and prove its effectiveness by a computational study. Results show that the proposed model can provide a CVaR optimal transportation path to hazmat multimodal transportation in realistic.

show abstract

“…In addition, Artzner et al (1999) introduced positive homogeneity and Kusuoka (2001) formally addressed the property of law invariance, which together naturally lead to the use of a measure known as conditional value at risk (CVaR) (see Artzner et al 1999, Rockafellar andUryasev 2000). Although the CVaR measure is now being used in a wide range of applications such as healthcare (see Chan et al 2014), supply chain (see Carneiro et al 2010), network design (see Babazadeh et al 2011), vehicle routing (see Toumazis and Kwon 2013), energy (see Jabr 2005), etc., there is still some resistance toward adopting such a measure as a gold standard. Perhaps one of the most important issues is that the class of CVaR measures can only capture a limited spectrum of risk attitudes and thus might not be able to accurately represent the risk aversion of some coherent decision or policy makers.…”

Section: Introductionmentioning

confidence: 99%

Minimizing Risk Exposure When the Choice of a Risk Measure Is Ambiguous

Delage

2018

Management Science

View full text Add to dashboard Cite

Abstract. Since the financial crisis of [2007][2008][2009], there has been a renewed interest in quantifying more appropriately the risks involved in financial positions. Popular risk measures such as variance and value-at-risk have been found inadequate because we now give more importance to properties such as monotonicity, convexity, translation invariance, positive homogeneity, and law invariance. Unfortunately, the challenge remains that it is unclear how to choose a risk measure that faithfully represents a decision maker's true risk attitude. In this work, we show that one can account precisely for (neither more nor less than) what we know of the risk preferences of an investor/policy maker when comparing and optimizing financial positions. We assume that the decision maker can commit to a subset of the above properties (the use of a law invariant convex risk measure for example) and that he can provide a series of assessments comparing pairs of potential risky payoffs. Given this information, we propose to seek financial positions that perform best with respect to the most pessimistic estimation of the level of risk potentially perceived by the decision maker. We present how this preference robust risk minimization problem can be solved numerically by formulating convex optimization problems of reasonable size. Numerical experiments on a portfolio selection problem, where the problem reduces to a linear program, will illustrate the advantages of accounting for the fact that the choice of a risk measure is ambiguous.

show abstract

Routing hazardous materials on time-dependent networks using conditional value-at-risk

Cited by 90 publications

References 50 publications

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

Dynamic conditional value-at-risk model for routing and scheduling of hazardous material transportation networks

Routing Hazmat Multimodal Transportation Based on CVaR Assessment

Minimizing Risk Exposure When the Choice of a Risk Measure Is Ambiguous

Contact Info

Product

Resources

About