Academic Journal

The Dual Simplex Method for Solving Bounded-Variable Linear Programs

Bibliographic Details
Title: The Dual Simplex Method for Solving Bounded-Variable Linear Programs
Authors: DJELOUD, Khalil
Source: Statistics, Optimization & Information Computing; Vol. 16 No. 3 (2026); 2509-2525 ; 2310-5070 ; 2311-004X
Publisher Information: International Academic Press
Publication Year: 2026
Collection: International Academic Press (IAPress)
Subject Terms: linear programming, long step rule, numerical experiments, open-source solver GLPK, dual simplex method
Description: In this paper, we {propose a novel and robust} dual simplex algorithm for solving bounded-variable linear programming based on a structured dual support framework and an enhanced long-step rule. The method enables stable and efficient updates of both the support and the associated co-solution. Its effectiveness is supported by a rigorous theoretical analysis: we prove a sign-preservation property of the support co-solutions and derive an explicit expression for the variation of the objective function, ensuring controlled and monotonic improvement and yielding strong convergence guarantees. Extensive experiments on NETLIB problems benchmarks demonstrate that the proposed approach is competitive with the dual simplex implementation of GLPK, confirming its efficiency and reliability.
Document Type: article in journal/newspaper
File Description: application/pdf
Language: English
Relation: https://iapress.org/index.php/soic/article/view/3489/2038; https://iapress.org/index.php/soic/article/view/3489
Availability: https://iapress.org/index.php/soic/article/view/3489
Rights: Copyright (c) 2026 Khalil DJELOUD ; https://creativecommons.org/licenses/by/4.0
Accession Number: edsbas.17DD91F7
Database: BASE
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