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Evolutionary Computation in Combinatorial Optimization

10th European Conference, EvoCOP 2010, Istanbul, Turkey, April 7-9, 2010, Proceedings

Constitutes the refereed proceedings of the 10th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2010, held in Instanbul, Turkey, in April 2010. This book discusses developments and applications in metaheuristics.

An Evolutionary Algorithm Guided by Preferences Elicited According to the
ELECTRE TRI Method Principles Eunice Oliveira1 and Carlos Henggeler
Antunes2 1 School of Technology and Management, Polytechnic Institute of
Leiria, Morro do ...

Evolutionary Computation in Practice

This book is loaded with examples in which computer scientists and engineers have used evolutionary computation - programs that mimic natural evolution - to solve many real-world problems. They aren’t abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions.

COMPUTATION. IN. PRACTICE. Tina Yu1 and Lawrence Davis2 1 2 Memorial
University of Newfoundland; VGO Associates
DeployingEvolutionaryComputation(EC)solutionstoreal-worldproblems involves
a wide spectrum of activities, ...

Evolutionary Computation in Bioinformatics

This book offers a definitive resource that bridges biology and evolutionary computation. The authors have written an introduction to biology and bioinformatics for computer scientists, plus an introduction to evolutionary computation for biologists and for computer scientists unfamiliar with these techniques.

Mol. Biol., 215:403-410. Anabarasu, L. A. (1998). Multiple sequence alignment
using parallel genetic algorithms. In The Second Asia-Pacific Conference on
Simulated Evolution (SEAL-98), Canberra, Australia (B. McKay, X. Yao, C. S.
Newton, ...

Applications of Evolutionary Computation in Chemistry

H. M. Cartwright: An Introduction to Evolutionary Computation andEvolutionary Algorithms; B. Hartke: Application of Evolutionary Algorithms to Global Cluster Geometry Optimization; K.D.M. Harris, R.L. Johnston, S. Habershon: Application of Evolutionary Computation in Structure Solution from Diffraction Data; S. M.

1 10 (2004): 1-32 DOI 10.1007/b 13931 An Introduction to Evolutionary
Computation and Evolutionary Algorithms Hugh M. Cartwright Physical and
Theoretical Chemistry Laboratory, Oxford University, South Parks Road, Oxford
OX 1 3QZ, UK ...

Genetic And Evolutionary Computation- GECCO 2004

Genetic And Evolutionary Computation Conference, Seattle, Wa, Usa, June 26-30, 2004, Proceedings

MostMOEAsuseadistancemetricorothercrowdingmethodinobjectivespaceinorder to maintain diversity for the non-dominated solutions on the Pareto optimal front. By ensuring diversity among the non-dominated solutions, it is possible to choose from a variety of solutions when attempting to solve a speci?c problem at hand. Supposewehavetwoobjectivefunctionsf (x)andf (x).Inthiscasewecande?ne 1 2 thedistancemetricastheEuclideandistanceinobjectivespacebetweentwoneighboring individuals and we thus obtain a distance given by 2 2 2 d (x, x )= f (x )?f (x )] + f (x )?f (x )] . (1) 1 2 1 1 1 2 2 1 2 2 f wherex andx are two distinct individuals that are neighboring in objective space. If 1 2 2 2 the functions are badly scaled, e.g. ?f (x)] ?f (x)], the distance metric can be 1 2 approximated to 2 2 d (x, x )? f (x )?f (x )] . (2) 1 2 1 1 1 2 f Insomecasesthisapproximationwillresultinanacceptablespreadofsolutionsalong the Pareto front, especially for small gradual slope changes as shown in the illustrated example in Fig. 1. 1.0 0.8 0.6 0.4 0.2 0 0 20 40 60 80 100 f 1 Fig.1.Forfrontswithsmallgradualslopechangesanacceptabledistributioncanbeobtainedeven if one of the objectives (in this casef ) is neglected from the distance calculations. 2 As can be seen in the ?gure, the distances marked by the arrows are not equal, but the solutions can still be seen to cover the front relatively well.

Genetic And Evolutionary Computation Conference, Seattle, Wa, Usa, June 26-
30, 2004, Proceedings Kalyanmoy Deb. A 10 × 10 board requires a neural
network with 100 inputs and 100 outputs, but is still simple enough to be solved
without ...

Evolutionary Computation

Theory and Applications

Evolutionary computation is the study of computational systems which use ideas and get inspiration from natural evolution and adaptation. This book is devoted to the theory and application of evolutionary computation. It is a self-contained volume which covers both introductory material and selected advanced topics. The book can roughly be divided into two major parts: the introductory one and the one on selected advanced topics. Each part consists of several chapters which present an in-depth discussion of selected topics. A strong connection is established between evolutionary algorithms and traditional search algorithms. This connection enables us to incorporate ideas in more established fields into evolutionary algorithms. The book is aimed at a wide range of readers. It does not require previous exposure to the field since introductory material is included. It will be of interest to anyone who is interested in adaptive optimization and learning. People in computer science, artificial intelligence, operations research, and various engineering fields will find it particularly interesting.

Some of the terminologies used in evolutionary computation have been
borrowed from these fields to reflect their connections, such as genetic algorithms
, genotypes, phenotypes, species, etc. Although the research in evolutionary ...

Practical Applications of Evolutionary Computation to Financial Engineering

Robust Techniques for Forecasting, Trading and Hedging

“Practical Applications of Evolutionary Computation to Financial Engineering” presents the state of the art techniques in Financial Engineering using recent results in Machine Learning and Evolutionary Computation. This book bridges the gap between academics in computer science and traders and explains the basic ideas of the proposed systems and the financial problems in ways that can be understood by readers without previous knowledge on either of the fields. To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others. Chapters 1 and 2 describe evolutionary computation. The third chapter is an introduction to financial engineering problems for readers who are unfamiliar with this area. The following chapters each deal, in turn, with a different problem in the financial engineering field describing each problem in detail and focusing on solutions based on evolutionary computation. Finally, the two appendixes describe software packages that implement the solutions discussed in this book, including installation manuals and parameter explanations.

To cement the ideas discussed in the book, software packages are offered that implement the systems described within. The book is structured so that each chapter can be read independently from the others.

Genetic and Evolutionary Computation for Image Processing and Analysis

Handbook of Evolutionary Computation

Many scientists and engineers now use the paradigms of evolutionary computation (genetic algorithms, evolution strategies, evolutionary programming, genetic programming, classifier systems, and combinations or hybrids) to tackle problems that are either intractable or unrealistically time consuming to solve through traditional computational strategies. The Handbook of Evolutionary Computation addresses the need for a comprehensive source of reference in the maturing field of evolutionary computation. The handbook is available in a looseleaf print format and an online format.

The Handbook of Evolutionary Computation addresses the need for a comprehensive source of reference in the maturing field of evolutionary computation. The handbook is available in a looseleaf print format and an online format.