Nature Inspired Cooperative Strategies for Optimization (NICSO 2007)

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Natalio Krasnogor, Vincenzo Nicosia, Mario Pavone, David Alejandro Pelta
Springer Science & Business Media, May 14, 2008 - Computers - 520 pages
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Biological and natural processes have been a continuous source of inspiration for the sciences and engineering. For instance, the work of Wiener in cybernetics was influenced by feedback control processes observable in biological systems; McCulloch and Pitts description of the artificial neuron was instigated by biological observations of neural mechanisms; the idea of survival of the fittest inspired the field of evolutionary algorithms and similarly, artificial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena.

The second International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), was held in Acireale, Italy, during November 8-10, 2007. The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

 

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Contents

A Preliminary Study of Fitness Inheritance in Evolutionary Constrained Optimization
1
Probabilistically Guided Prefix Gene Expression Programming
15
Flockingbased Document Clustering on the Graphics Processing Unit
27
Artificial Immune System for Collaborative Spam Filtering
39
MP Systems and Hybrid Petri Nets
52
Spatial Sorting of Binary Metadata Documents via NatureInspired Agents in Grids
63
hCHAC4 an ACO Algorithm for Solving the FourCriteria Military Pathfinding Problem
73
Searching Ground States of Ising Spin Glasses with Genetic Algorithms and Binary Particle Swarm Optimization
85
Learning Classifier System with Selfadaptive Discovery Mechanism
273
A Survey
284
Learning Robust Dynamic Networks in Prokaryotes by Gene Expression Networks Iterative Explorer GENIE
299
Discrete Particle Swarm Optimization for the Minimum Labelling Steiner Tree Problem
312
Ant Colony Cooperative Strategy in Electrocardiogram and Electroencephalogram Data Clustering
323
A Surface Tension and Coalescence Model for Dynamic Distributed Resources Allocation in Massively Parallel Processors onChip
335
Cooperative Learning Sensitive Agent System for Combinatorial Optimization
346
A Hybrid Genetic Algorithm for the Travelling Salesman Problem
357

A Hybrid System of Nature Inspired Metaheuristics
95
A New EvolutionarySwarm Cooperative Algorithm
105
Stabilizing Swarm Intelligence Search via Positive Feedback Resource Allocation
115
An Adaptive Metaheuristic for the Simultaneous Resolution of a Set of Instances
125
Honey Bees Mating Optimization Algorithm for the Vehicle Routing Problem
138
System Integration of a FixedPoint Swarm Coprocessor
149
Dynamic Adaptation of Genetic Operators Probabilities
159
Cooperative Coevolution Inspired Operators for Classical GP Schemes
169
Comparing the Neural and Immune Paradigms
179
An Architecture for Designing Natureinspired Cooperative Decentralized Heuristics
189
Memetic Algorithm for the Generalized Asymmetric Traveling Salesman Problem
199
Particle Swarm Based Collective Searching Model for Adaptive Environment
211
A New Nature Inspired Computational Framework for Multidimensional Search and Optimization
221
Social Impact based Approach to Feature Subset Selection
239
Influence of Different Deviations Allowed for Equality Constraints on Particle Swarm Optimization and Differential Evolution
249
Efficiency of Various Stochastic Optimization Algorithms in High Frequency Electromagnetic Applications
261
A BioInspired Model for Parsing of Natural Languages
368
An Evolutionary Approach for Performing Structural UnitTesting on ThirdParty ObjectOriented Java Software
379
Adaptive Spatial Allocation of Resource for Parallel Genetic Algorithm
389
3Colorability Problem
399
MultiConstraints Routing Algorithm Based on Swarm Intelligence over High Altitude Platforms
409
A Genetic Algorithm Framework Applied to Quantum Circuit Synthesis
419
A Method for Clustering Objects by their Contextual Specificity
431
An Evolutionary Based Production Planning and Scheduling System
443
Performance Analysis of Turning Process via Particle Swarm Optimization
453
Automatic Selection for the Beta Basis Function Neural Networks
461
A Problem of Generalization Which Works Best Large Population Size and Small Number of Generations or visa versa?
475
Detecting Hierarchical Organization in Complex Networks by Nearest Neighbor Correlation
486
A Genetic Algorithm Based on Complex Networks Theory for the Management of Airline Route Networks
495
Improved Genetic Algorithm
507
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Biological and natural processes have been a continuous source of inspiration for the sciences and engineering. For instance, the work of Wiener in cybernetics was influenced by feedback control processes observable in biological systems; McCulloch and Pitts description of the artificial neuron was instigated by biological observations of neural mechanisms; the idea of survival of the fittest inspired the field of evolutionary algorithms and similarly, artificial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena.

The second International Workshop on Nature Inspired Cooperative Strategies for Optimization (NICSO), was held in Acireale, Italy, during November 8-10, 2007. The aim for NICSO 2007 was to provide a forum were the latest ideas and state of the art research related to cooperative strategies for problem solving arising from Nature could be discussed. The contributions collected in this book were strictly peer reviewed by at least three members of the international programme committee, to whom we are indebted for their support and assistance. The topics covered by the contributions include several well established nature inspired techniques like Genetic Algorithms, Ant Colonies, Artificial Immune Systems, Evolutionary Robotics, Evolvable Systems, Membrane Computing, Quantum Computing, Software Self Assembly, Swarm Intelligence, etc.

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