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 e...

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Bibliographic Details
Published in2010 International Conference on Challenges in Environmental Science and Computer Engineering Vol. 1; pp. 410 - 413
Main Authors Liu, Yanwu, Zhang, Zhongzhen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.03.2010
Subjects
Conference management
Engineering management
Environmental management
large scale LP
Large-scale systems
Linear programming
Paper technology
pivoting algorithm
Standards development
Technology management
upper and lower bounds
Upper bound
Vectors
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Summary: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.
ISBN:1424459230
9780769539720
9781424459230
0769539726
DOI:10.1109/CESCE.2010.156