A New Approach of Attribute Reduction Based on Ant Colony Optimization

2009 ◽  
Author(s):  
Huanglin Zeng ◽  
Yan Huang ◽  
Xiaohui Zeng
Keyword(s):  
Ant Colony Optimization ◽  
Attribute Reduction ◽  
Ant Colony ◽  
New Approach

ACO powered by Local Searches Algorithms for the Solution of TSP Problems

2020 ◽  
Vol 1 (1) ◽  
pp. 1-10
Author(s):  
Nisreen L. Ahmed
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Technique ◽  
General Purpose ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
New Approach ◽  
Local Searches ◽  
Probabilistic Technique ◽  
The Social ◽  
Great Deluge Algorithm

Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the social behaviors of insects and other animals. Ants, in particular, have inspired a number of methods and techniques among which the most studied and successful is the general-purpose optimization technique, also known as ant colony optimization, In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.  Ant Colony Optimization (ACO) algorithm is used to arrive at the best solution for TSP. In this article, the researcher has introduced ways to use a great deluge algorithm with the ACO algorithm to increase the ability of the ACO in finding the best tour (optimal tour). Results are given for different TSP problems by using ACO with great deluge and other local search algorithms.

Evolving Ant Colony Optimization

1998 ◽  
Vol 01 (02n03) ◽  
pp. 149-159 ◽  
Author(s):  
Hozefa M. Botee ◽  
Eric Bonabeau
Keyword(s):  
Genetic Algorithm ◽  
Combinatorial Optimization ◽  
Ant Colony Optimization ◽  
Traveling Salesman Problem ◽  
Traveling Salesman ◽  
Ant Colony ◽  
New Approach ◽  
The Traveling Salesman Problem

Ant Colony Optimization (ACO) is a promising new approach to combinatorial optimization. Here ACO is applied to the traveling salesman problem (TSP). Using a genetic algorithm (GA) to find the best set of parameters, we demonstrate the good performance of ACO in finding good solutions to the TSP.

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