Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/30842
Title: Pre-scheduled colony size variation in dynamic environments
Authors: Mavrovouniotis, Michalis 
Ioannou, Anastasia 
Yang, Shengxiang 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Keywords: Economic and social effects;Optimization
Issue Date: 19-Apr-2017
Source: 20th European Conference on the Applications of Evolutionary Computation, EvoApplications 2017, Amsterdam, 19 - 21 April 2017
Conference: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 
Abstract: The performance of the MAX -MIN ant system (MMAS) in dynamic optimization problems (DOPs) is sensitive to the colony size. In particular, a large colony size may waste computational resources whereas a small colony size may restrict the searching capabilities of the algorithm. There is a trade off in the behaviour of the algorithm between the early and later stages of the optimization process. A smaller colony size leads to better performance on shorter runs whereas a larger colony size leads to better performance on longer runs. In this paper, pre-scheduling of varying the colony size of MMAS is investigated in dynamic environments.
URI: https://hdl.handle.net/20.500.14279/30842
ISBN: 9783319557915
ISSN: 03029743
DOI: 10.1007/978-3-319-55792-2_9
Rights: © Springer International Publishing AG
Type: Conference Papers
Affiliation : Nottingham Trent University 
University of Leicester 
De Montfort University 
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