Please use this identifier to cite or link to this item:
http://bura.brunel.ac.uk/handle/2438/5981
Title: | An immune system based genetic algorithm using permutation-based dualism for dynamic traveling salesman problems |
Authors: | Liu, L Wang, D Yang, S |
Keywords: | Dynamic environments;Genetic algorithms;Traveling salesman;Dualism |
Issue Date: | 2009 |
Publisher: | Springer Verlag |
Citation: | EvoWorkshops 2009: Applications of Evolutionary Computing, Lecture Notes in Computer Science 5484: 725 - 734, 2009 |
Abstract: | In recent years, optimization in dynamic environments has attracted a growing interest from the genetic algorithm community due to the importance and practicability in real world applications. This paper proposes a new genetic algorithm, based on the inspiration from biological immune systems, to address dynamic traveling salesman problems. Within the proposed algorithm, a permutation-based dualism is introduced in the course of clone process to promote the population diversity. In addition, a memory-based vaccination scheme is presented to further improve its tracking ability in dynamic environments. The experimental results show that the proposed diversification and memory enhancement methods can greatly improve the adaptability of genetic algorithms for dynamic traveling salesman problems. |
Description: | Copyright @ Springer-Verlag Berlin Heidelberg 2009. |
URI: | http://www.springerlink.com/content/a66r6654056027kx/ http://bura.brunel.ac.uk/handle/2438/5981 |
DOI: | http://dx.doi.org/10.1007/978-3-642-01129-0_82 |
ISSN: | 0302-9743 |
Appears in Collections: | Computer Science Dept of Computer Science Research Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Fulltext.pdf | 171.93 kB | Adobe PDF | View/Open |
Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.