Paper Info
Title
A Bee Colony Optimization Algorithm for Traveling Salesman Problem
Abstract
A Bee Colony Optimization (BCO) algorithm for Traveling Salesman Problem (TSP) is presented in this paper. TSP is a problem of finding a shortest closed tour which visits all the cities in a given set. The BCO model is constructed algorithmically based on the collective intelligence shown in bee foraging behaviour. This method uses a natural metaphor in making it as a optimization algorithm. Bees of an artificial colony are able to construct consecutively feasible tours by using information expressed in waggle dances. Experimental results comparing the proposed BCO model with some existing approaches on a set of benchmark problems are presented.
Year
DOI
Venue
2008
10.1109/AMS.2008.27
Asia International Conference on Modelling and Simulation
Keywords
Field
DocType
proposed bco model,optimization algorithm,bee colony optimization,consecutively feasible tour,collective intelligence,artificial colony,bee colony optimization algorithm,benchmark problem,bee foraging behaviour,salesman problem,bco model,computational modeling,approximation algorithms,computer aided manufacturing,traveling salesman problem,combinatorial optimization,computational intelligence,computer simulation
Ant colony optimization algorithms,Bottleneck traveling salesman problem,Artificial bee colony algorithm,Mathematical optimization,Extremal optimization,Computer science,Combinatorial optimization,Travelling salesman problem,2-opt,Metaheuristic
Conference
Citations 
PageRank 
References 
37
1.89
13
Authors
3
Name
Order
Citations
PageRank
Li-Pei Wong11098.32
Malcolm Yoke Hean Low269452.19
Chin Soon Chong331920.30