The paper presents a numerical method for computing the projections for Karmarkar's new algorithm for linear programming. The method is simple to implement, fully exploits sparsity, and appears in limited experimentation to have good stability properties. Preliminary numerical experience indicates that the method promises advantages over methods that refactor a matrix at every iteration.
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Queens Univ, Queens Canc Res Inst, Div Canc Care & Epidemiol, Kingston, ON K7L 3N6, CanadaQueens Univ, Queens Canc Res Inst, Div Canc Care & Epidemiol, Kingston, ON K7L 3N6, Canada
Groome, P
Schulze, K
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Queens Univ, Queens Canc Res Inst, Div Canc Care & Epidemiol, Kingston, ON K7L 3N6, CanadaQueens Univ, Queens Canc Res Inst, Div Canc Care & Epidemiol, Kingston, ON K7L 3N6, Canada
Schulze, K
Keller, S
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Queens Univ, Queens Canc Res Inst, Div Canc Care & Epidemiol, Kingston, ON K7L 3N6, CanadaQueens Univ, Queens Canc Res Inst, Div Canc Care & Epidemiol, Kingston, ON K7L 3N6, Canada
Keller, S
Mackillop, W
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Queens Univ, Queens Canc Res Inst, Div Canc Care & Epidemiol, Kingston, ON K7L 3N6, CanadaQueens Univ, Queens Canc Res Inst, Div Canc Care & Epidemiol, Kingston, ON K7L 3N6, Canada