Nonadjacent extreme point methods for solving linear programs

DOI10.1002/nav.3800300111zbMath0522.90057OpenAlexW2047184793MaRDI QIDQ3673477

Stafford G. Baines, Hanif D. Sherali, Allen L. Soyster

Publication date: 1983

Published in: Naval Research Logistics Quarterly (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/nav.3800300111

zbMATH Keywords

relaxation methodoptimal basisreduced gradient methodfeasible directions methodrandomly generated test problemsdual linear programsblock pivotingadvanced basisbinding hyperplanesnonadjacent extreme point methodsnumerical comparison of algorithmstwo phase simplex method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Linear programming (90C05)

Related Items (10)

An external reconstruction approach (ERA) to linear programming ⋮ Experiments with external pivoting ⋮ A two-phase support method for solving linear programs: numerical experiments ⋮ A computational study of redundancy in randomly generated polytopes ⋮ The sagitta method for solving linear programs ⋮ Solving large-scale linear programs by aggregation ⋮ LPAKO: A Simplex-based Linear Programming Program ⋮ A feasible direction method for linear programming ⋮ Intelligent gradient search in linear programming ⋮ Adjacent vertex simplex algorithms: More experimental results on random problems

Uses Software

• DEVEX

Cites Work

• The simplex algorithm with the pivot rule of maximizing criterion improvement
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