This book is the result of several years of research trying to better characterize parallel genetic algorithms (pGAs) as a powerful tool for optimization, search, and learning. Readers can learn how t
Cellular Genetic Algorithms defines a new class of optimization algorithms based on the concepts of structured populations and Genetic Algorithms (GAs). The authors explain and demonstrate the validi
Contains papers from a May 1994 workshop held in Hampton, Virginia, surveying recent developments in the field. Coverage includes core linear algebraic methods as well as tools more directly associate
This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition
New perspective technologies of genetic search and evolution simulation represent the kernel of this book. The authors wanted to show how these technologies are used for practical problems solution. T
This book covers the latest theories, applications and techniques in Biologically-Inspired Optimisation Methods. Many chapters derive from studies presented at workshops and international conferences
This work examines the challenges of distributed map merging and localization in multi-robot systems, which enables robots to acquire the knowledge of their surroundings needed to carry out coordinate
Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The boo
This is a comprehensive overview of the basics of fuzzy control, which also brings together some recent research results in soft computing, in particular fuzzy logic using genetic algorithms and neur
"This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. The book is unique in the sense of describing how a search t
This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, ca
This two volume set LNCS 8630 and 8631 constitutes the proceedings of the 14th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2014, held in Dalian, China, in
The objective in editing this book was to assemble a sample of the best work in parallel and distributed biologically inspired algorithms. The editors invited researchers in different domains to submi
The8thWorkshopontheFoundationsofGeneticAlgorithms,FOGA-8,washeld at the University of Aizu in Aizu-Wakamatsu City, Japan, January 5–9, 2005. This series of workshops was initiated in 1990 to encourage
The present study has attempted to apply the advantage of neuro-genetic algorithms for optimal decision making in maximum utilization of natural resources. Hydro-power is one of the inexpensive, but a
The advent of multi-core architectures and cloud-computing has brought parallel programming into the mainstream of software development. Unfortunately, writing scalable parallel programs using traditi
This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the a
Manufacturing systems, regardless of their size, have to work with scarce resources in dynamic environments. Managers are asked to assign production facilities over time to parallel activities respec
Evolutionary computation, a broad field that includes genetic algorithms, evolution strategies, and evolutionary programming, has proven to offer well-suited techniques for industrial and management t
The field of human genetics has witnessed tremendous acceleration in the last decade. The parallel advances in genotyping and sequencing technology, our understanding of human genetic variation, and t
This book is primarily intended as a research monograph that could also be used in graduate courses for the design of parallel algorithms in matrix computations.It assumes general but not extensive kn
This book focuses on architecture and implementation of algorithms, specifically on their real-time and causal processing implementation, architectures of FPGA design and parallel processing. It conc
Efficient Learning Machines explores all the major topics of machine learning, including big data, knowledge discovery, classifications, genetic algorithms, neural networking, kernel methods, and gami
This book covers up-to-date methods and algorithms for the automated analysis of engineering drawings and digital cartographic maps. The Non-Deterministic Agent System (NDAS) offers a parallel computa
Soft Computing is a complex of methodologies that includes artificial neural networks, genetic algorithms, fuzzy logic, Bayesian networks, and their hybrids. It admits approximate reasoning, imprecisi
This book provides a strong coverage of both the theoretical and application aspects of neural networks, fuzzy logic, genetic algorithms and hybrid intelligent techniques in robotics. Specific emphasi
