scholarly journals Leitmann’s direct method for fractional optimization problems

2010 ◽  
Vol 217 (3) ◽  
pp. 956-962 ◽  
Author(s):  
Ricardo Almeida ◽  
Delfim F.M. Torres
Keyword(s):  
Optimization Problems ◽  
Direct Method ◽  
Fractional Optimization

Chaotic crow search algorithm for fractional optimization problems

2018 ◽  
Vol 71 ◽  
pp. 1161-1175 ◽  
Author(s):  
Rizk M. Rizk-Allah ◽  
Aboul Ella Hassanien ◽  
Siddhartha Bhattacharyya
Keyword(s):  
Optimization Problems ◽  
Search Algorithm ◽  
Fractional Optimization

A BIOLOGICALLY INSPIRED NEURAL NETWORK FOR DYNAMIC PROGRAMMING

2001 ◽  
Vol 11 (06) ◽  
pp. 561-572 ◽  
Author(s):  
ROSELI A. FRANCELIN ROMERO ◽  
JANUSZ KACPRYZK ◽  
FERNANDO GOMIDE
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Dynamic Programming ◽  
Optimization Problems ◽  
Direct Method ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Biologically Inspired ◽  
The Neural Network ◽  
The Neural Networks

An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems.

Sign in / Sign up

Export Citation Format

Share Document