A probabilistic lower bound for two-stage stochastic programs

A probabilistic lower bound for two-stage stochastic programs [electronic resource]

In the framework of Benders decomposition for two-stage stochastic linear programs, the authors estimate the coefficients and right-hand sides of the cutting planes using Monte Carlo sampling. The authors present a new theory for estimating a lower bound for the optimal objective value and they comp...

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Bibliographic Details
Online Access: Online Access
Corporate Authors: Stanford University. Department of Operations Research (Researcher), United States. Department of Energy. Oakland Operations Office (Researcher)
Format: Government Document Electronic eBook
Language:English
Published: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Energy Research ; distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 1995.
Subjects:
Stochastic Processes.
Monte Carlo Method.
Limiting Values.
Optimization.
Algorithms.
Linear Programming.
Mathematics, Computers, Information Science, Management, Law, Miscellaneous.

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Call Number: E 1.99:SOL--95-6
E 1.99:SOL--95-6 Available

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