Evolutionary Computation In Dynamic And Uncertain Environments
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Evolutionary Computation in Dynamic and Uncertain Environments
Author: Shengxiang Yang
language: en
Publisher: Springer Science & Business Media
Release Date: 2007-03-07
This book compiles recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The book is motivated by the fact that some degree of uncertainty is inevitable in characterizing any realistic engineering systems. Discussion includes representative methods for addressing major sources of uncertainties in evolutionary computation, including handle of noisy fitness functions, use of approximate fitness functions, search for robust solutions, and tracking moving optimums.
Evolutionary Computation
Author: Wellington Santos
language: en
Publisher: BoD – Books on Demand
Release Date: 2009-10-01
This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field.
Optimization Algorithms
Author: Mykhaylo Andriychuk
language: en
Publisher: BoD – Books on Demand
Release Date: 2024-07-10
Optimization Algorithms - Classics and Last Advances is devoted to developing algorithm theory and exploring the use of different optimization algorithms for solving various problems in pure science, applied physics, and information technology. The book consists of two sections. The first focuses on developing abstract algorithms with subsequent applications to real-world optimization problems. It discusses optimization problems based on partial differential equations, canonical polyadic decomposition, variational approach, and ant colony optimization, which are discussed here. The second section presents problems related to optimization in information technologies. Chapters in this section address the utilization of optimization algorithms to solve problems of reducing computation time and computer memory, reducing kernel mechanism processing time in multimedia authoring tools, arranging access optimization for special applications, and minimizing resources for solving vehicle routing problems.