Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, GE

Authors:
Kaisa Miettinen;P. Neittaanmaki
Affiliations:
-;-
Venue:
Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, GE
Year:
1999

Citing 0
Cited 13

Worst-case tolerance design and quality assurance via genetic algorithms

Journal of Optimization Theory and Applications
Review of "How to solve it: Modern heuristics" by Zbigniew Michalewicz and David B. Fogel, Springer-Verlag 2000

Interfaces - Special issue: Franz Edelman award for achievement in operations research and the management sciences
Numerical Comparison of Some Penalty-Based Constraint Handling Techniques in Genetic Algorithms

Journal of Global Optimization
A massively parallel approach to deformable matching of 3D medical images via stochastic differential equations

Parallel Computing
A Novel Software Framework for Power-Aware Reconfiguration in Distributed Embedded Smart Cameras

ICPADS '06 Proceedings of the 12th International Conference on Parallel and Distributed Systems - Volume 1
A GA-based movie-on-demand platform using multiple distributed servers

Multimedia Tools and Applications
Chromosome reuse in genetic algorithms

GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
MulRoGA: A Multicast Routing Genetic Algorithm approach considering multiple objectives

Applied Intelligence
An interactive evolutionary algorithm for multiple objective convex integer problems

Proceedings of the 12th International Conference on Computer Systems and Technologies
Selection of optimal dimensionality reduction methods for face recognition using genetic algorithms

ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Optimizing the distributed network monitoring model with bounded bandwidth and delay constraints by neural networks

ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
Self-Evolvable Protocol Design Using Genetic Algorithms

International Journal of Applied Evolutionary Computation
Structural optimization of forest machines with hybridized nonsmooth and global methods

Structural and Multidisciplinary Optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

From the Publisher:Genetic algorithms (GA) and evolution strategies (ES) are relatively new stochastic based techniques for solving engineering problems on computers. GA and ES are based on a loose biological analogy: evolutionary theory (mutation, crossover, selection, survival of the fittest). Evolutionary algorithms encompass all adaptive and computational models of natural evolutionary systems - genetic algorithms, evolution strategies, evolutionary programming and genetic programming. In addition, they work well in the search for global solutions to optimization problems, allowing the production of optimization software that is robust and easy to implement. This book presents state of the art lectures delivered by international academic and industrial experts in the field of evolutionary computing. It bridges artificial intelligence and scientific computing with a particular emphasis on real-life problems encountered in application-oriented sectors, such as aerospace, electronics, telecommunications, energy and economics.