A new version of the improved primal simplex for degenerate linear programs

DOI10.1016/j.cor.2009.03.020zbMath1176.90646OpenAlexW1991749916MaRDI QIDQ733525

Dominique Orban, François Soumis, Vincent Raymond

Publication date: 16 October 2009

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

Full work available at URL: https://doi.org/10.1016/j.cor.2009.03.020

zbMATH Keywords

linear programmingdegeneracyprimal simplex

Mathematics Subject Classification ID

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

Related Items (10)

A linear programming decomposition focusing on the span of the nondegenerate columns ⋮ The positive edge criterion within COIN-OR's CLP ⋮ Customizing the solution process of COIN-OR's linear solvers with python ⋮ About the minimum mean cycle-canceling algorithm ⋮ The double pivot simplex method ⋮ Stabilized dynamic constraint aggregation for solving set partitioning problems ⋮ Column generation decomposition with the degenerate constraints in the subproblem ⋮ Improved Primal Simplex: A More General Theoretical Framework and an Extended Experimental Analysis ⋮ Integral Simplex Using Decomposition for the Set Partitioning Problem ⋮ Row-reduced column generation for degenerate master problems

Uses Software

• CPLEX

Cites Work

• Unnamed Item
• Multi-phase dynamic constraint aggregation for set partitioning type problems
• On the solution of highly degenerate linear programmes
• Pivot rules for linear programming: A survey on recent theoretical developments
• A basis-defiency-allowing variation of the simplex method for linear programming
• An Improved Primal Simplex Algorithm for Degenerate Linear Programs
• An Unsymmetric-Pattern Multifrontal Method for Sparse LU Factorization
• New Finite Pivoting Rules for the Simplex Method
• Simultaneous Vehicle and Crew Scheduling in Urban Mass Transit Systems
• Dynamic Aggregation of Set-Partitioning Constraints in Column Generation
• A Technique for Resolving Degeneracy in Linear Programming
• Optimality and Degeneracy in Linear Programming

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