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Advances in Genetic Programming

Advances in Genetic Programming
Author: Kenneth E. Kinnear (Jr.)
Publisher: MIT Press
Total Pages: 544
Release: 1994
Genre: Computers
ISBN: 9780262111881

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Advances in Genetic Programming reports significant results in improving the power of genetic programming, presenting techniques that can be employed immediately in the solution of complex problems in many areas, including machine learning and the simulation of autonomous behavior. Popular languages such as C and C++ are used in manu of the applications and experiments, illustrating how genetic programming is not restricted to symbolic computing languages such as LISP. Researchers interested in getting started in genetic programming will find information on how to begin, on what public-domain code is available, and on how to become part of the active genetic programming community via electronic mail.


Advances in Genetic Programming

Advances in Genetic Programming
Author: Kenneth E. Kinnear
Publisher: MIT Press
Total Pages: 504
Release: 1994
Genre: Computers
ISBN: 9780262194235

Download Advances in Genetic Programming Book in PDF, ePub and Kindle

Advances in Genetic Programming reports significant results in improving the power of genetic programming, presenting techniques that can be employed immediately in the solution of complex problems in many areas, including machine learning and the simulation of autonomous behavior. Popular languages such as C and C++ are used in manu of the applications and experiments, illustrating how genetic programming is not restricted to symbolic computing languages such as LISP. Researchers interested in getting started in genetic programming will find information on how to begin, on what public-domain code is available, and on how to become part of the active genetic programming community via electronic mail.


Advances in Genetic Programming

Advances in Genetic Programming
Author: Kenneth E. Kinnear
Publisher:
Total Pages:
Release: 1994
Genre: Computer programming
ISBN: 9780262111881

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Genetic Algorithms + Data Structures = Evolution Programs

Genetic Algorithms + Data Structures = Evolution Programs
Author: Zbigniew Michalewicz
Publisher: Springer Science & Business Media
Total Pages: 392
Release: 2013-03-09
Genre: Computers
ISBN: 3662033151

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Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.


Handbook of Genetic Programming Applications

Handbook of Genetic Programming Applications
Author: Amir H. Gandomi
Publisher: Springer
Total Pages: 589
Release: 2015-11-06
Genre: Computers
ISBN: 3319208837

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This contributed volume, written by leading international researchers, reviews the latest developments of genetic programming (GP) and its key applications in solving current real world problems, such as energy conversion and management, financial analysis, engineering modeling and design, and software engineering, to name a few. Inspired by natural evolution, the use of GP has expanded significantly in the last decade in almost every area of science and engineering. Exploring applications in a variety of fields, the information in this volume can help optimize computer programs throughout the sciences. Taking a hands-on approach, this book provides an invaluable reference to practitioners, providing the necessary details required for a successful application of GP and its branches to challenging problems ranging from drought prediction to trading volatility. It also demonstrates the evolution of GP through major developments in GP studies and applications. It is suitable for advanced students who wish to use relevant book chapters as a basis to pursue further research in these areas, as well as experienced practitioners looking to apply GP to new areas. The book also offers valuable supplementary material for design courses and computation in engineering.


Linear Genetic Programming

Linear Genetic Programming
Author: Markus F. Brameier
Publisher: Springer Science & Business Media
Total Pages: 323
Release: 2007-02-25
Genre: Computers
ISBN: 0387310304

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Linear Genetic Programming presents a variant of Genetic Programming that evolves imperative computer programs as linear sequences of instructions, in contrast to the more traditional functional expressions or syntax trees. Typical GP phenomena, such as non-effective code, neutral variations, and code growth are investigated from the perspective of linear GP. This book serves as a reference for researchers; it includes sufficient introductory material for students and newcomers to the field.


An Introduction to Genetic Algorithms

An Introduction to Genetic Algorithms
Author: Melanie Mitchell
Publisher: MIT Press
Total Pages: 226
Release: 1998-03-02
Genre: Computers
ISBN: 9780262631853

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Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics—particularly in machine learning, scientific modeling, and artificial life—and reviews a broad span of research, including the work of Mitchell and her colleagues. The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting "general purpose" nature of genetic algorithms as search methods that can be employed across disciplines. An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.


Genetic Algorithms and Engineering Design

Genetic Algorithms and Engineering Design
Author: Mitsuo Gen
Publisher: John Wiley & Sons
Total Pages: 436
Release: 1997-01-21
Genre: Technology & Engineering
ISBN: 9780471127413

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The last few years have seen important advances in the use ofgenetic algorithms to address challenging optimization problems inindustrial engineering. Genetic Algorithms and Engineering Designis the only book to cover the most recent technologies and theirapplication to manufacturing, presenting a comprehensive and fullyup-to-date treatment of genetic algorithms in industrialengineering and operations research. Beginning with a tutorial on genetic algorithm fundamentals andtheir use in solving constrained and combinatorial optimizationproblems, the book applies these techniques to problems in specificareas--sequencing, scheduling and production plans, transportationand vehicle routing, facility layout, location-allocation, andmore. Each topic features a clearly written problem description,mathematical model, and summary of conventional heuristicalgorithms. All algorithms are explained in intuitive, rather thanhighly-technical, language and are reinforced with illustrativefigures and numerical examples. Written by two internationally acknowledged experts in the field,Genetic Algorithms and Engineering Design features originalmaterial on the foundation and application of genetic algorithms,and also standardizes the terms and symbols used in othersources--making this complex subject truly accessible to thebeginner as well as to the more advanced reader. Ideal for both self-study and classroom use, this self-containedreference provides indispensable state-of-the-art guidance toprofessionals and students working in industrial engineering,management science, operations research, computer science, andartificial intelligence. The only comprehensive, state-of-the-arttreatment available on the use of genetic algorithms in industrialengineering and operations research . . . Written by internationally recognized experts in the field ofgenetic algorithms and artificial intelligence, Genetic Algorithmsand Engineering Design provides total coverage of currenttechnologies and their application to manufacturing systems.Incorporating original material on the foundation and applicationof genetic algorithms, this unique resource also standardizes theterms and symbols used in other sources--making this complexsubject truly accessible to students as well as experiencedprofessionals. Designed for clarity and ease of use, thisself-contained reference: * Provides a comprehensive survey of selection strategies, penaltytechniques, and genetic operators used for constrained andcombinatorial optimization problems * Shows how to use genetic algorithms to make production schedules,solve facility/location problems, make transportation/vehiclerouting plans, enhance system reliability, and much more * Contains detailed numerical examples, plus more than 160auxiliary figures to make solution procedures transparent andunderstandable


A Field Guide to Genetic Programming

A Field Guide to Genetic Programming
Author:
Publisher: Lulu.com
Total Pages: 252
Release: 2008
Genre: Computers
ISBN: 1409200736

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Genetic programming (GP) is a systematic, domain-independent method for getting computers to solve problems automatically starting from a high-level statement of what needs to be done. Using ideas from natural evolution, GP starts from an ooze of random computer programs, and progressively refines them through processes of mutation and sexual recombination, until high-fitness solutions emerge. All this without the user having to know or specify the form or structure of solutions in advance. GP has generated a plethora of human-competitive results and applications, including novel scientific discoveries and patentable inventions. This unique overview of this exciting technique is written by three of the most active scientists in GP. See www.gp-field-guide.org.uk for more information on the book.