Myrmecologische Nachrichten 6: 18; printable
- DOI: https://doi.org/10.25849/myrmecol.news_006:018
- Open Access: CC BY 4.0
- Year: 2004
- Title: Dorigo, M. & Stützle, T. 2004: Ant Colony Optimization
- Journal: Myrmecological News
- Volume: 6
- Pages: 18
- Type of contribution: Book Review
- Supplementary material: No
- Abstract: Dorigo, M. & STÜTZLE, T. 2004: Ant Colony Optimization. – The Mit Press, Cambridge Ma, 328 pp. Di Markus Waibel, Autonomous Systems Lab, Swiss Federal Institute of Technology, EPFL-STI-I2S-LSA2, CH-1015 Lausanne, Switzerland. E-mail: markus.waibel@epfl.ch Few people with an interest in biological system modelling have never heard of Ant Colony Optimization (ACO). It is the single, most well-known example of what has come to be called "bio-inspired" algorithms, and one of the most impressive success stories of translating biological phenomena into engineering solutions. The interest of Aco lies in its simplicity and versatility: It has been successfully applied to problems as diverse as network routing, industrial scheduling in metal casting and logistics with a nonhomogeneous fleet of trucks. In spite of ACO's huge success and its relevance to many fields outside computer science, up to now know-how of this field has been spread out over many scientific publications without an… Open access, licensed under CC BY 4.0. © 2004 The Author(s).
- Key words: None.
- Publisher: The Austrian Society of Entomofaunistics
- ISSN: Print: 1994-4136 - Online: 1997-3500