EconPapers    
Economics at your fingertips  
 

Revised Primal Simplex Algorithm

Nikolaos Ploskas and Nikolaos Samaras
Additional contact information
Nikolaos Ploskas: University of Macedonia
Nikolaos Samaras: University of Macedonia

Chapter Chapter 8 in Linear Programming Using MATLAB®, 2017, pp 329-381 from Springer

Abstract: Abstract The simplex algorithm is one of the top ten algorithms with the greatest influence in the twentieth century and the most widely used method for solving linear programming problems (LPs). Nearly all Fortune 500 companies use the simplex algorithm to optimize several tasks. This chapter presents the revised primal simplex algorithm. Numerical examples are presented in order for the reader to understand better the algorithm. Furthermore, an implementation of the algorithm in MATLAB is presented. The implementation is modular allowing the user to select which scaling technique, pivoting rule, and basis update method will use in order to solve LPs. Finally, a computational study over benchmark LPs and randomly generated sparse LPs is performed in order to compare the efficiency of the proposed implementation with MATLAB’s simplex algorithm.

Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:spochp:978-3-319-65919-0_8

Ordering information: This item can be ordered from
http://www.springer.com/9783319659190

DOI: 10.1007/978-3-319-65919-0_8

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-06-06
Handle: RePEc:spr:spochp:978-3-319-65919-0_8