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Convex Approximations of Chance Constrained Programs
SIAM Journal on Optimization, 2007We consider a chance constrained problem, where one seeks to minimize a convex objective over solutions satisfying, with a given close to one probability, a system of randomly perturbed convex constraints. This problem may happen to be computationally intractable; our goal is to build its computationally tractable approximation, i.e., an efficiently ...
Arkadi Nemirovski +1 more
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Chance constrained programming with fuzzy parameters
Fuzzy Sets and Systems, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Baoding Liu, Kakuzo Iwamura
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Chance Constrained Programming with Joint Constraints
Operations Research, 1965This paper considers the mathematical properties of chance constrained programming problems where the restriction is on the joint probability of a multivariate random event. One model that is considered arises when the right-handside constants of the linear constraints are random.
Miller, B. L., Wagner, H. M.
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Fuzzy Random Chance-Constrained Programming
IEEE Transactions on Fuzzy Systems, 2001By fuzzy random programming, we mean the optimization theory dealing with fuzzy random decision problems. This paper presents a new concept of chance of fuzzy random events, and constructs a general framework of fuzzy random chance-constrained programming.
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Chance Constrained Programming
2010Chance constrained programming was developed as a means of describing constraints in mathematical programming models in the form of probability levels of attainment. Consideration of chance constraints allows decision makers to consider mathematical programming objectives in terms of the probability of their attainment.
David L. Olson, Desheng Wu
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Joint chance-constrained dynamic programming
2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012This paper presents a novel joint chance-constrained dynamic programming algorithm, which explicitly bounds the probability of failure to satisfy given state constraints. Existing constrained dynamic programming approaches cannot handle a joint chance constraint since their application is limited to constraints in the same form as the cost function ...
Ono, Masahiro +2 more
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Chance-Constrained Programming with Joint Constraints
Operations Research, 1974Miller and Wagner have shown that a deterministic equivalent of a joint chance-constrained programming model with independent random right-hand-side elements is a concave programming problem. This paper obtains similar equivalents for chance-constrained programming models with coefficient matrices whose elements are normally distributed and with ...
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A Chance Constrained Multiple Choice Programming Algorithm
Operations Research, 1975This paper considers multiple choice programming problems in which the elements of the activity matrix can be normally distributed random variables or random vectors. The truncated block enumeration method of multiple choice programming is described and used in the development of an algorithm to solve problems of this type.
Ronald D. Armstrong, Joseph L. Balintfy
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Scenario Approximation of Robust and Chance-Constrained Programs
Journal of Optimization Theory and Applications, 2013zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Raffaello Seri, Christine Choirat
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On Distributionally Robust Chance-Constrained Linear Programs
Journal of Optimization Theory and Applications, 2006A stochastic linear programming problem is considered. Parameters of constraints are supposed stochastic, and the constraints at the solution point should be satisfied with the prescribed probability. It is shown in the paper that for a class of radially symmetric probability distributions deterministic counterpart is convex and can be constructed ...
Calafiore, G. C., Ghaoui, L. El
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