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Zbl 1154.90626
Dorigo, Marco; Blum, Christian
Ant colony optimization theory: a survey. (English)
[J] Theor. Comput. Sci. 344, No. 2-3, 243-278 (2005). ISSN 0304-3975

Summary: Research on a new metaheuristic for optimization is often initially focused on proof-of-concept applications. It is only after experimental work has shown the practical interest of the method that researchers try to deepen their understanding of the method's functioning not only through more and more sophisticated experiments but also by means of an effort to build a theory. Tackling questions such as ``how and why the method works'' is important, because finding an answer may help in improving its applicability. Ant colony optimization, which was introduced in the early 1990s as a novel technique for solving hard combinatorial optimization problems, finds itself currently at this point of its life cycle. With this article we provide a survey on theoretical results on ant colony optimization. First, we review some convergence results. Then we discuss relations between ant colony optimization algorithms and other approximate methods for optimization. Finally, we focus on some research efforts directed at gaining a deeper understanding of the behavior of ant colony optimization algorithms. Throughout the paper we identify some open questions with a certain interest of being solved in the near future.

MSC 2000:: *90C59 Approximation methods and heuristics
90-02 Research monographs (optimization)
68T05 Learning and adaptive systems
90C57 Polyhedral combinatorics, branch-and-bound, branch-and-cut
90C27 Combinatorial programming
68W25 Approximation algorithms

Keywords: ant colony optimization; metaheuristics; combinatorial optimization; convergence; stochastic gradient descent; model-based search; approximate algorithms

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Zentralblatt MATH Berlin [Germany]