Journal ArticleDOI
Response to Decision Problems Under Risk and Chance Constrained Programming: Dilemmas in the Transition
TLDR
It is shown that the analysis of a very simple artificial example contrived by its authors for a general indictment of all chance constrained programming is itself in error.Abstract:
Once again we show that the analysis of a very simple artificial example contrived by its authors for a general indictment of all chance constrained programming is itself in error. Proofs and further references are supplied below along with a discussion of other deficiencies and ambiguities in an article authored by A. J. Hogan, J. G. Morris and H. E. Thompson in Management Science, Vol. 27, No. 6 June 1981.read more
Citations
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Journal ArticleDOI
A hybrid inexact-stochastic water management model
TL;DR: The model is based on an inexact chance-constrained programming method, which improves upon the existing inexact and stochastic programming approaches by allowing both distribution information in B and uncertainties in A and C to be effectively incorporated within its optimization process.
Journal ArticleDOI
A fuzzy-stochastic robust programming model for regional air quality management under uncertainty
Lirong Liu,G H Huang,Y Liu +2 more
TL;DR: In this paper, a hybrid fuzzy-stochastic robust programming (FSRP) method is proposed to address complexities and uncertainties without unrealistic simplifications and applies it to a case study of regional air quality management.
Journal ArticleDOI
ITCLP: An inexact two-stage chance-constrained program for planning waste management systems
TL;DR: In this article, an inexact two-stage chance-constrained linear programming (ITCLP) method is developed for planning waste management systems, which can tackle uncertainties presented as both probability distributions and discrete intervals.
Journal ArticleDOI
A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty
TL;DR: In this article, a comprehensive review of energy management systems analysis and optimization modeling with the consideration of GHG emission reduction under uncertainty is presented, and a number of related methodologies and applications related to: (a) optimization modeling of GHGs emission mitigation; (b) optimization modelling of energy systems planning under uncertainty; and (c) model-based decision support tools are examined.
Journal ArticleDOI
Two-stage fuzzy chance-constrained programming: application to water resources management under dual uncertainties
Ping Guo,Guohe Huang +1 more
TL;DR: The results indicate that reasonable solutions were generated for objective function values and decision variables, thus a number of decision alternatives can be generated under different levels of stream flows, α-cut levels and fuzzy dominance indices.
References
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Journal ArticleDOI
On decision rules in stochastic programming
TL;DR: The paper surveys the basic results and nonresults for decision rules in stochastic programming and exhibits some of the difficulties encountered when trying to restrict the class of acceptable rules to those possessing specific functional forms.
Journal ArticleDOI
Decision Problems Under Risk and Chance Constrained Programming: Dilemmas in the Transition
TL;DR: In this paper, the authors compare CCP to stochastic programming with recourse SPR and conclude that CCP is seriously deficient as a modeling technique and of limited value as a computational device.
Journal ArticleDOI
Constrained Generalized Medians and Hypermedians as Deterministic Equivalents for Two-Stage Linear Programs under Uncertainty
TL;DR: In this paper, a deterministic equivalent for the original problem is presented, where the originally defined objective replaces all random variables by corresponding expected values and the remaining constraints do not contain any random terms.
Journal ArticleDOI
Stochastic Programming and Decision Analysis: An Apparent Dilemma
TL;DR: An example is given which demonstrates that using a decision theory analysis for the basic chance-constrained model of stochastic linear programming may lead to an apparent dilemma, namely, 0 > EVSI > EVPI.
Journal ArticleDOI
Note—A Comment on Blau's Dilemma in “Stochastic Programming” and Bayesian Decision Analysis
A. Charnes,W. W. Cooper +1 more
TL;DR: In this article, Blau proposed a chance constrained programming model for stochastic programming and decision analysis and showed that it leads to a dilemma in which EPVI, the expected value of perfect information, is less than EVSI, the Expected Value of sample information.
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