具有上界和下界的大规模线性规划的旋转算法

2010 International Conference on Challenges in Environmental Science and Computer Engineering Pub Date : 2010-03-06 DOI:10.1109/CESCE.2010.156

Yanwu Liu, Zhongzhen Zhang

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引用次数: 0

摘要

在实践中，线性规划(简化LP)问题往往是规模较大的问题。大规模LP需要具有高计算效率的算法来满足实际需要。LP的旋转算法可以有效地处理等式约束、自由变量约束和有上界和下界约束。特别是在计算过程中，该算法不需要添加任何辅助变量，既保持了LP的本质形式，又消除了辅助变量带来的多余计算。本文给出了具有上界和下界的LP的旋转算法的算法步骤，并通过一个简单的例子说明了该算法的过程。

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Pivoting Algorithm for Large Scale Linear Programming with Upper and Lower Bounds

The linear programming (simplified LP) problems in practice are always large scale. Large scale LP demands algorithms with high computing efficiency to satisfy practical needs. Pivoting algorithm for LP can cope with equality constraints, free variables, and constraints with upper and lower bounds efficiently. Especially during the course of computing, the algorithm need not add any auxiliary variables, which can keep the essential form of LP and eliminate the superfluous calculations caused by auxiliary variables. The paper presents the algorithmic steps of pivoting algorithm for LP with upper and lower bounds and demonstrates the process of the algorithm by a simple example.

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2010 International Conference on Challenges in Environmental Science and Computer Engineering

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