Paper Info
Title
Bee Colony Optimization with local search for traveling salesman problem
Abstract
Many real world industrial applications involve finding a Hamiltonian path with minimum cost. Some instances that belong to this category are transportation routing problem, scan chain optimization and drilling problem in integrated circuit testing and production. This paper presents a bee colony optimization (BCO) algorithm for traveling salesman problem (TSP). The BCO model is constructed algorithmically based on the collective intelligence shown in bee foraging behaviour. The model is integrated with 2-opt heuristic to further improve prior solutions generated by the BCO model. Experimental results comparing the proposed BCO model with existing approaches on a set of benchmark problems are presented.
Year
DOI
Venue
2010
10.1109/INDIN.2008.4618252
International Journal on Artificial Intelligence Tools
Keywords
Field
DocType
optimisation,integrated circuit testing,transportation routing problem,traveling salesman problem,hamiltonian path,travelling salesman problems,scan chain optimization,collective intelligence,local search,drilling problem,bee colony optimization,metaheuristic,integrated circuit,combinatorial optimization
Bottleneck traveling salesman problem,Ant colony optimization algorithms,Mathematical optimization,Extremal optimization,Computer science,Combinatorial optimization,Artificial intelligence,2-opt,Local search (optimization),Optimization problem,Machine learning,Metaheuristic
Journal
Volume
Issue
ISSN
19
3
1935-4576 E-ISBN : 978-1-4244-2171-8
ISBN
Citations 
PageRank 
978-1-4244-2171-8
9
0.62
References 
Authors
15
3
Name
Order
Citations
PageRank
Li-Pei Wong11098.32
Malcolm Yoke Hean Low269452.19
Chin Soon Chong331920.30