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SOLVING LARGE SCALE LINEAR PROGRAMMING PROBLEMS USING AN INTERIOR POINT METHOD ON A MASSIVELY PARALLEL SIMD COMPUTER

 

作者: HJÁLMTYÝR HAFSTEINSSON,   RONI LEVKOVITZ,   GAUTAM MITRA,  

 

期刊: Parallel Algorithms and Applications  （Taylor Available online 1994）
卷期: Volume 4, issue 3-4  

页码: 301-316

 

ISSN:1063-7192

 

年代: 1994

 

DOI:10.1080/10637199408915470

 

出版商: Taylor & Francis Group

 

关键词: Cholesky factorization;interior point methods;linear programming;parallel computers;SIMD machines;sparse matrix factorization;G.1.3.

 

数据来源: Taylor

 

摘要:

The interior point method (IPM) is now well established as a competitive technique for solving very large scale linear programming problems. The leading variant of the interior point method is the primal dual—predictor corrector algorithm due to Mehrotra. The main computational steps of this algorithm are the repeated calculation and solution of a large sparse positive definite system of equations

 

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