A new neural network for solving linear programming problems

DOI10.1016/0377-2217(96)00044-6zbMath0912.90215OpenAlexW2072915961WikidataQ60487018 ScholiaQ60487018MaRDI QIDQ1268155

Andrzej Cichocki, K. Weinzierl, Rolf Unbehauen, Robert W. Hölzel

Publication date: 25 May 1999

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(96)00044-6

zbMATH Keywords

neural networkparallel computingstochastic gradient descent optimization

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Linear programming (90C05) Parallel numerical computation (65Y05)

Related Items

Solving convex programming problems with equality constaints by neural networks ⋮ A neural network approach to multiobjective and multilevel programming problems ⋮ Solving nonlinear complementarity problems with neural networks: A reformulation method approach ⋮ A Novel Recurrent Neural Network with Finite-Time Convergence for Linear Programming

Uses Software

• OSL

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• A new polynomial-time algorithm for linear programming
• A deterministic annealing neural network for convex programming
• Neural networks for solving linear inequality systems
• Neural networks for linear inverse problems with incomplete data especially in applications to signal and image reconstruction
• Method of 'penalty' functions and the foundations of Pyne's method
• The gradient method of solving convex programmig problems on electronic analog computers
• Path-Following Methods for Linear Programming
• Analysis and design of a recurrent neural network for linear programming
• Implementing the simplex method for the Optimization Subroutine Library

This page was built for publication: A new neural network for solving linear programming problems