By Gautam Mitra, Mehrdad Tamiz, Joseph Yadegar
Communications of the ACM,
December 1988,
Vol. 31 No. 12, Pages 1474-1482
10.1145/53580.214953
Comments
A feasible direction method for solving Linear Programming (LP) problems, followed by a procedure for purifying a non-basic solution to an improved extreme point solution have been embedded within an otherwise simplex based optimizer. The algorithm is designed to be hybrid in nature and exploits many aspects of sparse matrix and revised simplex technology. The interior search step terminates at a boundary point which is usually non-basic. This is followed by a series of minor pivotal steps which lead to a basic feasible solution with a superior objective function value. It is concluded that the procedures discussed in this article are likely to have three possible applications, which are
- (i) improving a non-basic feasible solution to a superior extreme point solution,
- (ii) an improved starting point for the revised simplex method, and
- (iii) an efficient implementation of the multiple price strategy of the revised simplex method.
The full text of this article is premium content
No entries found
Log in to Read the Full Article
Need Access?
Please select one of the options below for access to premium content and features.
Create a Web Account
If you are already an ACM member, Communications subscriber, or Digital Library subscriber, please set up a web account to access premium content on this site.
Join the ACM
Become a member to take full advantage of ACM's outstanding computing information resources, networking opportunities, and other benefits.
Subscribe to Communications of the ACM Magazine
Get full access to 50+ years of CACM content and receive the print version of the magazine monthly.
Purchase the Article
Non-members can purchase this article or a copy of the magazine in which it appears.
