Capacity Expansion Problem by Monte Carlo Sampling Method
2009 ◽
Vol 13
(6)
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pp. 697-703
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We consider the stochastic programming problem with recourse in which the expectation of the recourse function requires a large number of function evaluations, and its application to the capacity expansion problem. We propose an algorithm which combines an L-shaped method and a Monte Carlo method. The importance sampling technique is applied to obtain variance reduction. In the previous approach, the recourse function is approximated as an additive form in which the function is separable in the components of the stochastic vector. In our approach, the approximate additive form of the recourse function is perturbed to define the new density function. Numerical results for the capacity expansion problem are presented.
2011 ◽
Vol 88-89
◽
pp. 554-558
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1999 ◽
Vol 06
(02)
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pp. 185-202
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1992 ◽
Vol 96
(3)
◽
pp. 1911-1918
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2018 ◽
Vol 98
◽
pp. 11-26
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1994 ◽
Vol 40
(12)
◽
pp. 2216-2222
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2020 ◽
Vol 16
(10)
◽
pp. 6645-6655
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