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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zufferey, N. |
| Copyright Year | 2014 |
| Description | Author affiliation: HEC, Univ. of Geneva, Geneva, Switzerland (Zufferey, N.) |
| Abstract | Ant algorithms are well-known metaheuristics which have been widely studied and used since two decades. Generally, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. The goal of this paper is on the one hand to classify and benchmark the ant algorithms, and on the other hand to put forward the successful elements of these methods. Moreover, the performance of the different types of ant algorithms is evaluated according to several criteria, and not only according to the quality of the obtained solutions. |
| Sponsorship | IBM |
| Starting Page | 339 |
| Ending Page | 343 |
| File Size | 149205 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781479927296 |
| ISSN | 10666192 |
| DOI | 10.1109/PDP.2014.69 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-02-12 |
| Publisher Place | Italy |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Force Classification algorithms Equations Optimization Heuristic algorithms Robustness population-based metaheuristics ant algorithms |
| Content Type | Text |
| Resource Type | Article |
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