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E-raamat: Handbook of Swarm Intelligence: Concepts, Principles and Applications

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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.



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.

Arvustused

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

Part A Particle Swarm Optimization
From Theory to Practice in Particle Swarm Optimization
3(34)
Maurice Clerc
What Makes Particle Swarm Optimization a Very Interesting and Powerful Algorithm?
37(30)
J.L. Fernandez-Martinez
E. Garcia-Gonzalo
Developing Niching Algorithms in Particle Swarm Optimization
67(22)
Xiaodong Li
Test Function Generators for Assessing the Performance of PSO Algorithms in Multimodal Optimization
89(30)
Julio Barrera
Carlos A. Coello Coello
Linkage Sensitive Particle Swarm Optimization
119(14)
Deepak Devicharan
Chilukuri K. Mohan
Parallel Particle Swarm Optimization Algorithm Based on Graphic Processing Units
133(22)
Ying Tan
You Zhou
Velocity Adaptation in Particle Swarm Optimization
155(20)
Sabine Helwig
Frank Neumann
Rolf Wanka
Integral-Controlled Particle Swarm Optimization
175(26)
Zhihua Cui
Xingjuan Cai
Ying Tan
Jianchao Zeng
Particle Swarm Optimization for Markerless Full Body Motion Capture
201(20)
Zheng Zhang
Hock Soon Seah
Chee Kwang Quah
An Adaptive Multi-Objective Particle Swarm Optimization Algorithm with Constraint Handling
221(20)
Praveen Kumar Tripathi
Sanghamitra Bandyopadhyay
Sankar Kumar Pal
Multiobjective Particle Swarm Optimization for Optimal Power Flow Problem
241(28)
M.A. Abido
A Multi-objective Resource Assignment Problem in Product Driven Supply Chain Using Quantum Inspired Particle Swarm Algorithm
269(26)
Sri Krishna Kumar
S.G. Ponnambalam
M.K. Tiwari
Part B Bee Colony Optimization
Honeybee Optimisation - An Overview and a New Bee Inspired Optimisation Scheme
295(34)
Konrad Diwold
Madeleine Beekman
Martin Middendorf
Parallel Approaches for the Artificial Bee Colony Algorithm
329(18)
Rafael Stubs Parpinelli
Cesar Manuel Vargas Benitez
Heitor Silverio Lopes
Bumble Bees Mating Optimization Algorithm for the Vehicle Routing Problem
347(26)
Yannis Marinakis
Magdalene Marinaki
Part C Ant Colony Optimization
Ant Colony Optimization: Principle, Convergence and Application
373(16)
Haibin Duan
Optimization of Fuzzy Logic Controllers for Robotic Autonomous Systems with PSO and ACO
389(32)
Oscar Castillo
Patricia Melin
Fevrier Valdez
Ricardo Martinez-Marroquin
Part D Other Swarm Techniques
A New Framework for Optimization Based-On Hybrid Swarm Intelligence
421(30)
Pei-Wei Tsai
Jeng-Shyang Pan
Peng Shi
Bin-Yih Liao
Glowworm Swarm Optimization for Multimodal Search Spaces
451(18)
K.N. Krishnanand
D. Ghose
Direct and Inverse Modeling of Plants Using Cat Swarm Optimization
469(18)
Ganapati Panda
Pyari Mohan Pradhan
Babita Majhi
Parallel Bacterial Foraging Optimization
487(16)
S. S. Pattnaik
K.M. Bakwad
S. Devi
B.K. Panigrahi
Sanjoy Das
Reliability-Redundancy Optimization Using a Chaotic Differential Harmony Search Algorithm
503(14)
Leandro dos Santos Coelho
Diego L. de A. Bernert
Viviana Cocco Mariani
Gene Regulatory Network Identification from Gene Expression Time Series Data Using Swarm Intelligence
517(26)
Debasish Datta
Amit Konar
Swagatam Das
B.K. Panigrahi
Author Index 543