A novel algorithm of stochastic chance-constrained linear programming and its application
type: Item
instance of: scholarly article
title: A novel algorithm of stochastic chance-constrained linear programming and its application
zbMATH Open document ID: 1264.90128
DOI: 10.1155/2012/139271
author: Xiaodong Ding
author: Cheng-liang Wang
published in: Mathematical Problems in Engineering
publication date: 2013-06-11T00:00:00Z
review text: Summary: The computation problem is discussed for the stochastic chance-constrained linear programming, and a novel direct algorithm, that is, simplex algorithm based on stochastic simulation, is proposed. The considered programming problem in this paper is linear programming with chance constraints and random coefficients, and therefore the stochastic simulation is an important implement of the proposed algorithm. By theoretical analysis, the theory basis of the proposed algorithm is obtained and, by numerical examples, the feasibility and validness of this algorithm are illustrated. The detailed algorithm procedure is given, which is easily converted into the executable codes of software tools. Then, we compare it with some algorithms to verify its superiority. Finally, a practical example is presented to show its practicability.
Mathematics Subject Classification ID: 90C15
Mathematics Subject Classification ID: 90C05
zbMATH DE Number: 6173049
Wikidata QID: Q58912476
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2012/139271
OpenAlex ID: W2015920112
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description: scientific article; zbMATH DE number 6173049