Hybrid-LP: finding advanced starting points for simplex, and pivoting LP methods

DOI10.1016/j.cor.2010.07.001zbMath1231.90287OpenAlexW2071119412MaRDI QIDQ709179

Camelia Al-Najjar, Behnam B. Malakooti

Publication date: 15 October 2010

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2010.07.001

zbMATH Keywords

linear programmingextreme pointgradient methodcomputational efficiencysimplexpivotingadaptiveinitializationhybrid LPinterior direction

Mathematics Subject Classification ID

Linear programming (90C05) Interior-point methods (90C51) Extreme-point and pivoting methods (90C49)

Related Items (3)

Three nearly scaling-invariant versions of an exterior point algorithm for linear programming ⋮ Improving a primal–dual simplex-type algorithm using interior point methods ⋮ A triangulation and fill-reducing initialization procedure for the simplex algorithm

Uses Software

• CONOPT
• MarPlex
• NETLIB LP Test Set

Cites Work

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• An infeasible (exterior point) simplex algorithm for assignment problems
• A note on ``An improved initial basis for the simplex algorithm
• Experiments with external pivoting
• Computational behavior of a feasible direction method for linear programming
• The simplex algorithm with a new primal and dual pivot rule
• Comments on An efficient search direction for linear programming problems by H. Luh and R. Tsaih.
• Pivot versus interior point methods: Pros and cons
• A new efficient primal dual simplex algorithm
• A lower bound on the average number of pivot-steps for solving linear programs. Valid for all variants of the simplex-algorithm
• An improved initial basis for the simplex algorithm
• CONOPT: A GRG code for large sparse dynamic nonlinear optimization problems
• Dealing with degeneracy in reduced gradient algorithms
• Two direct methods in linear programming
• An efficient search direction for linear programming problems

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