EconPapers    
Economics at your fingertips  
 

Improvement and its computer implementation of an artificial-free simplex-type algorithm by Arsham

Pei-wang Gao

Applied Mathematics and Computation, 2015, vol. 263, issue C, 410-415

Abstract: Arsham ever described a new phase 1 simplex-type algorithm which allegedly obviates the use of artificial variables. Soon after, Enge and Huhn gave a counterexample, in which Arsham’s algorithm declares the infeasibility of a feasible problem. For this reason, this paper proposes an improvement of Arsham’s algorithm to make it work well, which is searching for the nonbasic variables into the basic variable set (BVS) column by column in only one pivot sequence from beginning to end in order to decrease computational time spent by many repeated searching sequences after each iteration. Next, when the BVS is complete, the phase 1 algorithm ends with a feasible basic solution; otherwise, two variants are presented to pivot the artificial variables out of the basis. The idea of variant 1 is making all artificial variables in basis minimized in turn while maintaining the BVS feasible in the pivoting process. In variant 2, the objective is to minimize the sum of all artificial variables in basis while keeping basic variables (including artificial) feasible. Finally, a computer implementation is accomplished to test the efficiency of our improvement comparing to the ordinary simplex algorithm on some standard test instances and randomly generated problems. The computational results show that our improved algorithms averagely spends much less executive time at each iteration than the ordinary simplex algorithm on sparse linear programming problems, and variant 2 is also competitive on dense linear programming problems.

Keywords: Linear programming; Simplex method; Phase 1; Artificial variable; Basic variable set (BVS) (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0096300315005391
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:263:y:2015:i:c:p:410-415

DOI: 10.1016/j.amc.2015.04.077

Access Statistics for this article

Applied Mathematics and Computation is currently edited by Theodore Simos

More articles in Applied Mathematics and Computation from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:apmaco:v:263:y:2015:i:c:p:410-415