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JACIII Vol.13 No.6 pp. 697-703
doi: 10.20965/jaciii.2009.p0697
(2009)

Paper:

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Capacity Expansion Problem by Monte Carlo Sampling Method

Takayuki Shiina

Chiba Institute of Technology, 2-17-1 Tsudanuma, Narashino, Chiba 275-0016, Japan

Received:
June 25, 2008
Accepted:
March 25, 2009
Published:
November 20, 2009
Creative Commons License
Keywords:
stochastic programming with recourse, Monte Carlo method, importance sampling, capacity expansion problem.
Abstract
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.
Cite this article as:
T. Shiina, “Capacity Expansion Problem by Monte Carlo Sampling Method,” J. Adv. Comput. Intell. Intell. Inform., Vol.13 No.6, pp. 697-703, 2009.
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