Journal ArticleDOI
Risk-averse two-stage stochastic programming with an application to disaster management
TLDR
This study considers a risk-averse two-stage stochastic programming model, where the conditional-value-at-risk (CVaR) as the risk measure and constructs two decomposition algorithms based on the generic Benders-decomposition approach to solve problems in the presence of variability risk measures.About:
This article is published in Computers & Operations Research.The article was published on 2012-03-01. It has received 327 citations till now. The article focuses on the topics: Stochastic programming & Stochastic optimization.read more
Citations
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Journal ArticleDOI
Supply chain network design under uncertainty: A comprehensive review and future research directions
TL;DR: A comprehensive review of studies in the fields of SCND and reverse logistics network design under uncertainty and existing optimization techniques for dealing with uncertainty such as recourse-based stochastic programming, risk-averse stochastics, robust optimization, and fuzzy mathematical programming are explored.
Journal ArticleDOI
Selection of resilient supply portfolio under disruption risks
TL;DR: In this paper, a mixed integer programming approach is proposed to determine risk-neutral, risk-averse or mean-risk supply portfolios, with conditional value-at-risk applied to control the risk of worst-case cost.
Journal ArticleDOI
Literature review of humanitarian logistics research: trends and challenges
Adriana Leiras,Irineu de Brito,Eduardo Queiroz Peres,Tábata Rejane Bertazzo,Hugo Tsugunobu Yoshida Yoshizaki +4 more
TL;DR: In this paper, a literature review of humanitarian logistics (HL) that aims to identify trends and suggest some directions for future research is presented, and the main conclusions are the need for more studies into the disaster recovery phase and the need to closer relationships between academia and humanitarian organizations to increase the number of applied research.
Journal ArticleDOI
Drones for disaster response and relief operations: A continuous approximation model
TL;DR: This paper proposes a Continuous Approximation model that designs the potentiality of drones as a mode of transportation to supply emergency commodities in a disaster-affected region and conducts extensive sensitivity analysis to reveal insights into how system design varies with key drone design parameters.
Journal ArticleDOI
Stochastic network models for logistics planning in disaster relief
TL;DR: A new two-stage stochastic network flow model to help decide how to rapidly supply humanitarian aid to victims of a disaster within this context is developed and it is demonstrated that the heuristic performs well for real and random instances.
References
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Journal ArticleDOI
Coherent Measures of Risk
TL;DR: In this paper, the authors present and justify a set of four desirable properties for measures of risk, and call the measures satisfying these properties "coherent", and demonstrate the universality of scenario-based methods for providing coherent measures.
Journal ArticleDOI
Optimization of conditional value-at-risk
R. T. Rockafellar,S Uryasev +1 more
TL;DR: In this paper, a new approach to optimize or hedging a portfolio of financial instruments to reduce risk is presented and tested on applications, which focuses on minimizing Conditional Value-at-Risk (CVaR) rather than minimizing Value at Risk (VaR), but portfolios with low CVaR necessarily have low VaR as well.
BookDOI
Introduction to Stochastic Programming
John R. Birge,Franois Louveaux +1 more
TL;DR: This textbook provides a first course in stochastic programming suitable for students with a basic knowledge of linear programming, elementary analysis, and probability to help students develop an intuition on how to model uncertainty into mathematical problems.
Book
AMPL: A Modeling Language for Mathematical Programming
Robert Fourer,Brian W. Kernighan +1 more
TL;DR: An efficient translator is implemented that takes as input a linear AMPL model and associated data, and produces output suitable for standard linear programming optimizers.
Journal ArticleDOI
Conditional value-at-risk for general loss distributions
TL;DR: Fundamental properties of conditional value-at-risk are derived for loss distributions in finance that can involve discreetness and provides optimization shortcuts which, through linear programming techniques, make practical many large-scale calculations that could otherwise be out of reach.