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TNN
2008
108views more  TNN 2008»
13 years 4 months ago
A Novel Recurrent Neural Network for Solving Nonlinear Optimization Problems With Inequality Constraints
This paper presents a novel recurrent neural network for solving nonlinear optimization problems with inequality constraints. Under the condition that the Hessian matrix of the ass...
Youshen Xia, Gang Feng, Jun Wang
TNN
2010
182views Management» more  TNN 2010»
12 years 11 months ago
A discrete-time neural network for optimization problems with hybrid constraints
Abstract--Recurrent neural networks have become a prominent tool for optimizations including linear or nonlinear variational inequalities and programming, due to its regular mathem...
Huajin Tang, Haizhou Li, Zhang Yi
IJON
2008
177views more  IJON 2008»
13 years 4 months ago
An asynchronous recurrent linear threshold network approach to solving the traveling salesman problem
In this paper, an approach to solving the classical Traveling Salesman Problem (TSP) using a recurrent network of linear threshold (LT) neurons is proposed. It maps the classical ...
Eu Jin Teoh, Kay Chen Tan, H. J. Tang, Cheng Xiang...
GECCO
2005
Springer
196views Optimization» more  GECCO 2005»
13 years 10 months ago
Breeding swarms: a new approach to recurrent neural network training
This paper shows that a novel hybrid algorithm, Breeding Swarms, performs equal to, or better than, Genetic Algorithms and Particle Swarm Optimizers when training recurrent neural...
Matthew Settles, Paul Nathan, Terence Soule
ICRA
1998
IEEE
142views Robotics» more  ICRA 1998»
13 years 8 months ago
Lagrangian Relaxation Neural Networks for Job Shop Scheduling
Abstract--Manufacturing scheduling is an important but difficult task. In order to effectively solve such combinatorial optimization problems, this paper presents a novel Lagrangia...
Peter B. Luh, Xing Zhao, Yajun Wang