Paper Info
Title
Ant Supervised By Pso And 2-Opt Algorithm, As-Pso-2opt, Applied To Traveling Salesman Problem
Abstract
AS-PSO-2Opt is a new enhancement of the AS-PSO method. In the classical AS-PSO, the Ant heuristic is used to optimize the tour length of a Traveling Salesman Problem, TSP, and PSO is applied to optimize three parameters of ACO, (alpha,beta,rho). The AS-PSO-2Opt consider a post processing resuming path redundancy, helping to improve local solutions and to decrease the probability of falling in local minimum. Applied to TSP, the method allowed retrieving a valuable path solution and a set of fitted parameters for ACO. The performance of the AS-PSO-2Opt is tested on nine different TSP test benches. Experimental results based on a statistical analysis showed that the new proposal performs better than key state of art methods using Genetic algorithm, Neural Network and ACO algorithm. The AS-PSO-2Opt performs better than close related methods such as PSO-ACO-3Opt [9] and ACO with ABC [19] for various test benches.
Year
Venue
Keywords
2016
2016 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
AS-PSO, AS-PSO-2Opt, TSP, PSO, ACO
Field
DocType
ISSN
Computer science,Redundancy (engineering),Travelling salesman problem,Artificial intelligence,Artificial neural network,Cybernetics,Genetic algorithm,Particle swarm optimization,Mathematical optimization,Heuristic,Algorithm,2-opt,Machine learning
Conference
1062-922X
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Sonia Kefi121.74
Nizar Rokbani2296.80
Krömer Pavel333059.99
Mohamed Adel Alimi41947217.16