Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/70057
Title: Dynamically updating the exploiting parameter in improving performance of ant-based algorithms
Authors: Dinh, H.T.
Mamun, A.A. 
Dinh, H.T.
Keywords: Ant Colony Optimization
Ant System
Combinatorial Op-timization Problem
Traveling Salesman Problem
Issue Date: 2005
Source: Dinh, H.T.,Mamun, A.A.,Dinh, H.T. (2005). Dynamically updating the exploiting parameter in improving performance of ant-based algorithms. Lecture Notes in Computer Science 3521 : 340-349. ScholarBank@NUS Repository.
Abstract: The utilization of pseudo-random proportional rule to balance between the exploitation and exploration of the search process was shown in Ant Colony System (ACS) algorithm. In ACS, this rule is governed by a parameter so-called exploiting parameter which is always set to a constant value. Besides, all ACO-based algorithm either omit this rule or applying it with a fixed value of the exploiting parameter during the runtime of algorithms. In this paper, this rule is adopted with a simple dynamical updating technique for the value of that parameter. Moreover, experimental analysis of incorporating a technique of dynamical updating for the value of this parameter into some state-of-the-art Ant-based algorithms is carried out. Also computational results on Traveling Salesman Problem benchmark instances are represented which probably show that Ant-based implementations with local search procedures gain a better performance if the dynamical updating technique is used. © Springer-Verlag Berlin Heidelberg 2005.
Source Title: Lecture Notes in Computer Science
URI: http://scholarbank.nus.edu.sg/handle/10635/70057
ISSN: 03029743
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

16
checked on Dec 16, 2017

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.