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2010 | OriginalPaper | Chapter

9. Pheromone-Balance Driven Ant Colony Optimization with Greedy Mechanism

Author : Masaya Yoshikawa

Published in: Machine Learning and Systems Engineering

Publisher: Springer Netherlands

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Abstract

Ant colony optimization (ACO), which has been based on the feeding behavior of ants, has a powerful solution searching ability. However, since processing must be repeated many times, the computation process also requires a very long time. In this chapter, we discuss a new ACO algorithm that incorporates adaptive greedy mechanism to shorten the processing time. The proposed algorithm switches two selection techniques adaptively according to generation. In addition, the new pheromone update rules are introduced in order to control the balance of the intensification and diversification. Experiments using benchmark data prove the validity of the proposed algorithm.

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Literature
1.
M. Dorigo, V. Maniezzo, A. Colorni, Ant system: optimization by a colony of cooperating agents. IEEE Trans. Syst. Man Cybern. Part B. 26(1), 29–41 (1996)CrossRef
2.
M. Dorigo, L.M. Gambardella, Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans. Evol. Comput. 1(1), 53–66 (1997)CrossRef
3.
T.H. Ahmed, Simulation of mobility and routing in ad hoc networks using ant colony algorithms. Proc. Int. Conf. Inf. Technol. Coding Comput. 2, 698–703 (2005)
4.
M. Yoshikawa, H. Terai, A Hybrid Ant Colony Optimization Technique for Job-Shop Scheduling Problems, Proc. of 4th IEEE/ACIS International Conference on Software Engineering Research, Management & Applications (SERA 2006), 95–100 (2006)
5.
A. Hara, T. Ichimura, N. Fujita, T. Takahama, “Effective Diversification of Ant-Based Search Using Colony Fission and Extinction”, Proc, of IEEE Congress on Evolutionary Computation (CEC 2006), 1028–1035 (2006)
6.
Z. Ren, Z. Feng, Z. Zhang, GSP-ANT: an efficient ant colony optimization algorithm with multiple good solutions for pheromone update. Proc. IEEE Int. Conf. Intelligent Comput. Intelligent Syst. 1, 589–592 (2009)
7.
G. Shang, J. Xinzi, T. Kezong, “Hybrid Algorithm Combining Ant Colony Optimization Algorithm with Genetic Algorithm”, Proc. of Chinese Control Conference (CCC 2007), 701–704 (2007)
8.
Y.-H. Wang, P.-Z. Pan, A Novel Bi-Directional Convergence Ant Colony Optimization with SA for Job-Shop Scheduling, Proc. of International Conference on Computational Intelligence and Software Engineering (CiSE 2009), 1–4 (2009)
9.
J. Holland, Adaptation in Natural Artificial Systems, 2nd edn. (The University of Michigan Press, MIT Press, 1992)
10.
D.E. Goldberg, Genetic Algorithms in Search Optimization, and Machine Learning (Addison Wesley, Reading MA, 1989)MATH
11.
R.A. Rutenbar, Simulated annealing algorithms: an overview. IEEE Circuits Dev. Mag. 5(1), 19–26 (1989)CrossRef
Metadata
Title
Pheromone-Balance Driven Ant Colony Optimization with Greedy Mechanism
Author
Masaya Yoshikawa
Copyright Year
2010
Publisher
Springer Netherlands
Book
Machine Learning and Systems Engineering

Print ISBN: 978-90-481-9418-6

Electronic ISBN: 978-90-481-9419-3

Copyright Year: 2010

DOI
https://doi.org/10.1007/978-90-481-9419-3_9

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