Primal–dual solution for the linear programming problems using neural networks

2005 ◽  
Vol 167 (1) ◽  
pp. 198-211 ◽  
Author(s):  
A. Malek ◽  
A. Yari
Keyword(s):  
Neural Networks ◽  
Linear Programming ◽  
Dual Solution ◽  
Primal Dual ◽  
Linear Programming Problems

A primal-dual method for linear programming problems with fuzzy variables

2010 ◽  
Vol 4 (2) ◽  
pp. 189 ◽  
Author(s):  
A. Ebrahimnejad ◽  
S.H. Nasseri ◽  
F. Hosseinzadeh Lotfi ◽  
M. Soltanifar
Keyword(s):  
Linear Programming ◽  
Dual Method ◽  
Fuzzy Variables ◽  
Primal Dual ◽  
Linear Programming Problems

A least-squares primal-dual algorithm for solving linear programming problems

2002 ◽  
Vol 30 (5) ◽  
pp. 289-294 ◽  
Author(s):  
Earl Barnes ◽  
Victoria Chen ◽  
Balaji Gopalakrishnan ◽  
Ellis.L. Johnson
Keyword(s):  
Linear Programming ◽  
Least Squares ◽  
Dual Algorithm ◽  
Primal Dual ◽  
Linear Programming Problems

ON SOLVING SHORTEST PATHS WITH A LEAST-SQUARES PRIMAL-DUAL ALGORITHM

2008 ◽  
Vol 25 (02) ◽  
pp. 135-150
Author(s):  
I.-LIN WANG
Keyword(s):  
Linear Programming ◽  
Least Squares ◽  
Shortest Path ◽  
Shortest Paths ◽  
Arc Length ◽  
Dual Algorithm ◽  
Shortest Path Problems ◽  
Dijkstra's Algorithm ◽  
Primal Dual ◽  
Linear Programming Problems

Recently a new least-squares primal-dual (LSPD) algorithm, that is impervious to degeneracy, has effectively been applied to solving linear programming problems by Barnes et al., 2002. In this paper, we show an application of LSPD to shortest path problems with nonnegative arc length is equivalent to the Dijkstra's algorithm. We also compare the LSPD algorithm with the conventional primal-dual algorithm in solving shortest path problems and show their difference due to degeneracy in solving the 1-1 shortest path problems.

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