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Ant Colonies: Behavior in Insects and Computer Applications
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Editors: Emily C. Sun
Book Description:
Ant colony optimization is a population-based general-search technique that can be used for the solution of difficult combinatorial problems. Ant colony optimization uses the knowledge-reinforcing mechanism used by real-life ants while traversing possible paths in search of food, depositing a chemical substance (called pheromone), en-route and subsequently forming trails which can then be followed by other ants in the colony. With its strong mathematical foundation and its simplicity of use, ant colony optimization provides an alternative method to routing optimizations with a wide range of applications. This book presents topical research in the study of ant colonies, their behavior and application in computer technologies. (Imprint: Nova)

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Table of Contents:

Progressive Organization of Co-Operating Colonies/Collections of Ants/Agents (POOCA) for Competent Pheromone-Based Navigation and Multi-Agent Learning, pp. 1-50
(Tatiana Tambouratzis, Department of Industrial Management & Technology, University of Piraeus, Greece, and others)

Ant Colony Solution to the Optimal Transformer Sizing and Efficiency Problem in Power Systems, pp. 51-107
(Marina A. Tsili, Eleftherios I. Amoiralis, Faculty of Electrical & Computer Engineering, National Technical University of Athens, University Campus, Athens, Greece, and others)

Distributed Decisions: New Insights from Radio-Tagged Ants, pp. 109-128
(Elva J. H. Robinson, Wlodek Mandecki, York Centre for Complex Systems Analysis and Department of Biology, University of York, United Kingdom, and others)

Impacts, Ecology and Dispersal of the Invasive Argentine Ant ^, pp. 129-156
(Eiriki Sunamura, Shun Suzuki, Hironori Sakamoto, Koji Nishisue, Mamoru Terayama and Sadahiro Tatsuki, Graduate School of Agricultural and Life Sciences, University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan, and others)

Ant Colony Optimization used in No Wavefront Sensor Adaptive Optics Systems for Solid-State Lasers, pp. 157-169
(Lizhi Dong, Ping Yang, Xiang Lei, Wenjin Liu, Hu Yan, Bing Xu, Laboratory on Adaptive Optics, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu, China, and others)

Any Colony Optimization Agents and Path Routing: The Cases of Construction Scheduling and Urban Water Distribution Pipe Networks, pp. 171-194
(S. Christodoulou, G. Ellinas, Univ. of Cyprus, Nicosia, Cyprus)

KANTS: A Self-Organized Ant System for Pattern Clustering and Classification, pp. 195-211
(A.M. Mora, C. Fernandes, J.J. Merelo, Department of Architecture and Computer Technology, University of Granada, Spain)

A Hybrid System Based in Ant Colony and Paraconsistent Logic ^, pp. 213-243
(Luiz Eduardo da Silva, Germano Lambert-Torresy, Ricardo Menezes Salgadoz, Humberto C´esar Brand˜ao de Oliveirax, Alfenas Federal University, and others)

Ant Colony Optimization: A Powerful Strategy for Biomarker Feature Selection, pp. 245-249
(Weixiang Zhao, Cristina E. Davis, Department of Mechanical and Aerospace Engineering, University of California, David, California)*

Any Colony Optimization Based Message Authentication for Wireless Networks, pp. 251-264
(N.K. Sreelaja, G.A.Vijayalakshmi Pai, Department of Mathematics and Computer Applications, PSG College of Technology, Coimbatore, India)*


      Computer Science, Technology and Applications
      Animal Science, Issues and Professions
   Binding: Hardcover
   Pub. Date: 2011
   Pages: 7x10 (NBC - R) 274pp.
   ISBN: 978-1-61122-023-0
   Status: AV
Status Code Description
AN Announcing
FM Formatting
PP Page Proofs
FP Final Production
EP Editorial Production
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Ant Colonies: Behavior in Insects and Computer Applications