Kategoria BISAC: Computers >> Programming - Algorithms

Evolutionary algorithms (EAs) are becoming increasingly attractive for researchers from various disciplines, such as operations research, computer science, industrial engineering, electrical engineering, social science, economics, etc. This book presents an insightful, comprehensive, and up-to-date treatment of EAs, such as genetic algorithms, differential evolution, evolution strategy, constraint optimization, multimodal optimization, multiobjective optimization, combinatorial optimization, evolvable hardware, estimation of distribution algorithms, ant colony optimization,...

This book constitutes the proceedings of the 14th International Workshop on Computer Algebra in Scientific Computing, CASC 2013, held in Berlin, Germany, in September 2013. The 33 full papers presented were carefully reviewed and selected for inclusion in this book.

The papers address issues such as polynomial algebra; the solution of tropical linear systems and tropical polynomial systems; the theory of matrices; the use of computer algebra for the investigation of various mathematical and applied topics related to ordinary differential equations (ODEs); applications of symbolic...

• The book deals with some of the most important and challenging areas of programming and computer science, but in a highly pedagogic and readable manner.
• The book covers both algorithmic theory and programming practice, demonstrating how theory is...

Every area of science and engineering today has to process voluminous data sets. Using exact, or even approximate, algorithms to solve intractable problems in critical areas, such as computational biology, takes time that is exponential in some of the underlying parameters. Parallel computing addresses this issue and has become affordable with the advent of multicore architectures. However, programming multicore machines is much more difficult due to oddities existing in the architectures.

Offering insights into different facets of this area, Multicore Computing:...

The contributions in this volume are written by the foremost international researchers and practitioners in the GP arena. They examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.

Topics include: FINCH: A System for Evolving Java, Practical Autoconstructive Evolution, The Rubik Cube and GP Temporal Sequence Learning, Ensemble classifiers: AdaBoost and Orthogonal Evolution of Teams, Self-modifying...

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 validity of these cellular genetic algorithms throughout the book. This class of genetic algorithms is shown to produce impressive results on a whole range of domains, including complex problems that are epistatic, multi-modal, deceptive, discrete, continuous, multi-objective, and random in nature. The focus of this book is twofold. On the one hand, the authors present new algorithmic models and...