Results 221 to 230 of about 5,851 (265)

On the ‘Bayesability’ of chance-constrained programming problems

Operations Research Letters, 1986
It was hoped that the aversions to risks of goal-attainment failures modeled by chance constraints could be equivalently embodied in some von Neumann-Morgenstern utility function, the expectation of which could be maximized in the standard Bayesian fashion to yield solution sets at all chance-constraint levels identical to those of the original chance-
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Mixed Strategies in Chance-Constrained Programming

Journal of the Operational Research Society, 1980
In usual stochastic programming problems involving randomly distributed "resources" and chance constraints, decision variables are taken as deterministic. With the help of simple illustrations involving a single decision variable, Vajda and Greenberg showed that minimum expected values could be made smaller by treating the decision variable as random ...
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A note on chance constrained programming with fuzzy coefficients

Fuzzy Sets and Systems, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baoding Liu, Kakuzo Iwamura
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Randomized Decisions in Chance-Constrained Programming

Journal of the Operational Research Society, 1985
Routine use of convex optimization leads to solutions for a class of problems concerning randomized decisions in chance-constrained programming that have previously yielded to ad hoc methods.
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Chance Constrained Programming

1976
Whereas two-stage problems, as we have seen in the last chapter, are rather well-behaved from the viewpoint of optimization theory as far as convexity, continuity and differentiability are concerned, this is in general not true for chance constrained programming problems.
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Chance-constrained programming on sugeno measure space

Expert Systems with Applications, 2011
Uncertain programming is a theoretical tool to handle optimization problems under uncertain environment, it is mainly established in probability, possibility, or credibility measure spaces. Sugeno measure space is an interesting and important extension of probability measure space.
Hong Zhang, Minghu Ha, Hong-Jie Xing
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A Note on Chance-Constrained Programming

Journal of the Operational Research Society, 1983
A stochastic linear programme with chance constraints is considered. By allowing for the possibility of sampling, a so-called dynamic statistical decision model is developed, and the existence of an optimal decision rule is shown under appropriate continuity and compactness assumptions.
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Data-driven chance constrained stochastic program

Mathematical Programming, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ruiwei Jiang, Yongpei Guan
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A chance-constrained programming algorithm

BIT, 1972
This paper describes a new algorithm solving the deterministic equivalents of chance-constrained problems where the random variables are normally distributed and independent of each other. In this method nonlinear chance-constraints are first replaced by uniformly tighter linear constraints.
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JOINT CHANCE CONSTRAINED PROGRAMMING WITH DEPENDENT PARAMETERS

Advances and Applications in Statistics, 2018
Summary: In this paper, we consider joint chance constrained programming (JCCP) technique, where two probabilistic constraints are required to jointly satisfy at least the tolerance measure a. We introduce a suggested approach to obtain an equivalent deterministic model for probabilistic model with joint chance constraints (JCCs) when the RHS ...
Hafez, Nada, El-Dash, Afaf, Albehery, Nagwa   +2 more
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