Handbook of Swarm Intelligence: Concepts, Principles and Applications

ISBN-13: 9783642173899 / Angielski / Twarda / 2011 / 544 str.

Bijaya Ketan Panigrahi;Yuhui Shi;Meng-Hiot Lim

Opis

Recent work on the behavior of swarming creatures such as bees posits an innate collective intelligence that gives rise to myriad computational problem-solving techniques. This volume is both an introduction to the topic and a survey of leading-edge research.

Recenzje

Aus den Rezensionen:

"... ist das kollektive, intelligent erscheinende Verhalten eines aus dezentralen ... Die Einheiten sind sich üblicherweise dieses kollektiven Verhaltens nicht bewusst ... Es richtet sich an Wissenschaftler, Ingenieure und Studierende, die sich mit SI-Algorithmen und deren Anwendung befassen. ... Die meisten Beiträge sind theoretischer Natur, aber einige behandeln auch praktische Fragestellungen ..." (in: Bulletin SEV/VSE ITG-Sonderausgabe, 2011, Vol. 102, S. 44)

Spis treści

Part A: Particle Swarm Optimization.- Part B: Bee Colony Optimization.- Part C: Ant  Colony Optimization.-Part D: Other Swarm Techniques.

Blurb

From nature, we observe swarming behavior in the form of ant colonies, bird flocking, animal herding, honey bees, swarming of bacteria, and many more.  It is only in recent years that researchers have taken notice of such natural swarming systems as culmination of some form of innate collective intelligence, albeit swarm intelligence (SI) - a metaphor that inspires a myriad of computational problem-solving techniques.  In computational intelligence, swarm-like algorithms have been successfully applied to solve many real-world problems in engineering and sciences. This handbook volume serves as a useful foundational as well as consolidatory state-of-art collection of articles in the field from various researchers around the globe.  It has a rich collection of contributions pertaining to the theoretical and empirical study of single and multi-objective variants of swarm intelligence based algorithms like particle swarm optimization (PSO), ant colony optimization (ACO), bacterial foraging optimization algorithm (BFOA), honey bee social foraging algorithms, and harmony search (HS).  With chapters describing various applications of SI techniques in real-world engineering problems, this handbook can be a valuable resource for researchers and practitioners, giving an in-depth flavor of what SI is capable of achieving.