-

 

 

 




Optimization Online





 

A quadratic penalty algorithm for linear programming and its application to linearizations of quadratic assignment problems

I. L. Galabova (I.L.Galabova***at***sms.ed.ac.uk)
J. A. J. Hall (J.A.J.Hall***at***ed.ac.uk)

Abstract: This paper provides the first meaningful documentation and analysis of an established technique which aims to obtain an approximate solution to linear programming problems prior to applying the primal simplex method. The underlying algorithm is a penalty method with naive approximate minimization in each iteration. During initial iterations an approach similar to augmented Lagrangian is used. Later the technique corresponds closely to a classical quadratic penalty method. There is also a discussion of the extent to which it can be used to obtain fast approximate solutions of LP problems, in particular when applied to linearizations of quadratic assignment problems.

Keywords: Linear programming; quadratic penalty methods; quadratic assignment problems

Category 1: Linear, Cone and Semidefinite Programming (Linear Programming )

Citation:

Download: [PDF]

Entry Submitted: 04/24/2018
Entry Accepted: 04/25/2018
Entry Last Modified: 11/05/2018

Modify/Update this entry


  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository

 

Submit
Update
Policies
Coordinator's Board
Classification Scheme
Credits
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society