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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
ISSN: 03029743
Appears in Collections:Staff Publications

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