Sparse Matrix Techniques in Two Mathematical Programming Codes

By Stanford University. Department of Operations Research. Operations Research House

Sparse Matrix Techniques in Two Mathematical Programming Codes
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The authors empirically compared ten pivot selection rules for representing the inverse of a sparse basis in triangularized product form. On examples drawn from actual applications, one of the rules yield inverses that were only slightly less sparse than the original basis. The rule was used in the M5 mathematical programming system and has resulted in substantial reduction in running time.

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