Immune-based algorithms for dynamic optimization

被引：50
作者：
Trojanowski, Krzysztof [1 ]
Wierzchon, Slawomir T. [1 ]
机构：
[1] Polish Acad Sci, Inst Comp Sci, PL-01237 Warsaw, Poland
来源：
INFORMATION SCIENCES | 2009年 / 179卷 / 10期
关键词：
Clonal selection; Heuristic optimization; Dynamic optimization; MUTATIONS; NETWORKS;
D O I：
10.1016/j.ins.2008.11.014
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The main problem with biologically inspired algorithms (like evolutionary algorithms or particle swarm optimization) when applied to dynamic optimization is to force their readiness for continuous search for new optima occurring in changing locations. Immune-based algorithm, being an instance of an algorithm that adapt by innovation seem to be a perfect candidate for continuous exploration of a search space. In this paper we describe various implementations of the immune principles and we compare these instantiations on complex environments. (c) 2008 Elsevier Inc. All rights reserved.
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收藏
页码：1495 / 1515
页数：21
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