Métaheuristiques pour l'ordonnancement multicritère et les problèmes de transport 

Métaheuristiques pour l'ordonnancement multicritère et les problèmes de transport  PDF Author: JARBOUI Bassem
Publisher: Lavoisier
ISBN: 2746295237
Category :
Languages : en
Pages : 323

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Book Description
Pour assurer une production de biens de qualité, de manière fiable et dans des délais maîtrisés, les organisations ont besoin d’outils d'exécution optimale de tâches tels que l’ordonnancement. Le succès des méthodologies de résolution des problèmes d’ordonnancement de production basées sur les métaheuristiques s’explique par leur capacité à fournir des solutions proches de l’optimum, dans des temps raisonnables. Cet ouvrage se consacre, dans un premier temps, aux métaheuristiques appliquées aux problèmes d’ordonnancement multicritère, qui sont des cas particuliers des problèmes d’optimisation combinatoire multicritère, généralement NP-difficiles. Puis, il s’intéresse aux préoccupations d’ordonnancement dans le secteur du transport qui suscitent également de multiples problèmes d’optimisation. Deux grands domaines d’application se distinguent, celui des systèmes de transport et celui des ressources de transport intervenant dans un atelier.

Métaheuristiques pour l'ordonnancement multicritère et les problèmes de transport 

Métaheuristiques pour l'ordonnancement multicritère et les problèmes de transport  PDF Author: JARBOUI Bassem
Publisher: Lavoisier
ISBN: 2746295237
Category :
Languages : en
Pages : 323

Get Book Here

Book Description
Pour assurer une production de biens de qualité, de manière fiable et dans des délais maîtrisés, les organisations ont besoin d’outils d'exécution optimale de tâches tels que l’ordonnancement. Le succès des méthodologies de résolution des problèmes d’ordonnancement de production basées sur les métaheuristiques s’explique par leur capacité à fournir des solutions proches de l’optimum, dans des temps raisonnables. Cet ouvrage se consacre, dans un premier temps, aux métaheuristiques appliquées aux problèmes d’ordonnancement multicritère, qui sont des cas particuliers des problèmes d’optimisation combinatoire multicritère, généralement NP-difficiles. Puis, il s’intéresse aux préoccupations d’ordonnancement dans le secteur du transport qui suscitent également de multiples problèmes d’optimisation. Deux grands domaines d’application se distinguent, celui des systèmes de transport et celui des ressources de transport intervenant dans un atelier.

An Introduction to Genetic Algorithms

An Introduction to Genetic Algorithms PDF Author: Melanie Mitchell
Publisher: MIT Press
ISBN: 0262631857
Category : Computers
Languages : en
Pages : 213

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Book Description
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.

The Practical Handbook of Genetic Algorithms

The Practical Handbook of Genetic Algorithms PDF Author: Lance D. Chambers
Publisher: CRC Press
ISBN: 9781420050073
Category : Mathematics
Languages : en
Pages : 442

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Book Description
The mathematics employed by genetic algorithms (GAs)are among the most exciting discoveries of the last few decades. But what exactly is a genetic algorithm? A genetic algorithm is a problem-solving method that uses genetics as its model of problem solving. It applies the rules of reproduction, gene crossover, and mutation to pseudo-organism

Genetic Algorithm Essentials

Genetic Algorithm Essentials PDF Author: Oliver Kramer
Publisher: Springer
ISBN: 331952156X
Category : Technology & Engineering
Languages : en
Pages : 94

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Book Description
This book introduces readers to genetic algorithms (GAs) with an emphasis on making the concepts, algorithms, and applications discussed as easy to understand as possible. Further, it avoids a great deal of formalisms and thus opens the subject to a broader audience in comparison to manuscripts overloaded by notations and equations. The book is divided into three parts, the first of which provides an introduction to GAs, starting with basic concepts like evolutionary operators and continuing with an overview of strategies for tuning and controlling parameters. In turn, the second part focuses on solution space variants like multimodal, constrained, and multi-objective solution spaces. Lastly, the third part briefly introduces theoretical tools for GAs, the intersections and hybridizations with machine learning, and highlights selected promising applications.

Introduction to Genetic Algorithms

Introduction to Genetic Algorithms PDF Author: S.N. Sivanandam
Publisher: Springer Science & Business Media
ISBN: 3540731903
Category : Technology & Engineering
Languages : en
Pages : 453

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Book Description
This book offers a basic introduction to genetic algorithms. It provides a detailed explanation of genetic algorithm concepts and examines numerous genetic algorithm optimization problems. In addition, the book presents implementation of optimization problems using C and C++ as well as simulated solutions for genetic algorithm problems using MATLAB 7.0. It also includes application case studies on genetic algorithms in emerging fields.

Genetic Algorithms and Genetic Programming

Genetic Algorithms and Genetic Programming PDF Author: Michael Affenzeller
Publisher: CRC Press
ISBN: 1420011324
Category : Computers
Languages : en
Pages : 395

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Book Description
Genetic Algorithms and Genetic Programming: Modern Concepts and Practical Applications discusses algorithmic developments in the context of genetic algorithms (GAs) and genetic programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for al

Genetic Algorithms

Genetic Algorithms PDF Author: Kim-Fung Man
Publisher: Springer Science & Business Media
ISBN: 9781852330729
Category : Mathematics
Languages : en
Pages : 364

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Book Description
This comprehensive book gives a overview of the latest discussions in the application of genetic algorithms to solve engineering problems. Featuring real-world applications and an accompanying disk, giving the reader the opportunity to use an interactive genetic algorithms demonstration program.

Genetic Algorithms in Elixir

Genetic Algorithms in Elixir PDF Author: Sean Moriarity
Publisher: Pragmatic Bookshelf
ISBN: 168050830X
Category : Computers
Languages : en
Pages : 304

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Book Description
From finance to artificial intelligence, genetic algorithms are a powerful tool with a wide array of applications. But you don't need an exotic new language or framework to get started; you can learn about genetic algorithms in a language you're already familiar with. Join us for an in-depth look at the algorithms, techniques, and methods that go into writing a genetic algorithm. From introductory problems to real-world applications, you'll learn the underlying principles of problem solving using genetic algorithms. Evolutionary algorithms are a unique and often overlooked subset of machine learning and artificial intelligence. Because of this, most of the available resources are outdated or too academic in nature, and none of them are made with Elixir programmers in mind. Start from the ground up with genetic algorithms in a language you are familiar with. Discover the power of genetic algorithms through simple solutions to challenging problems. Use Elixir features to write genetic algorithms that are concise and idiomatic. Learn the complete life cycle of solving a problem using genetic algorithms. Understand the different techniques and fine-tuning required to solve a wide array of problems. Plan, test, analyze, and visualize your genetic algorithms with real-world applications. Open your eyes to a unique and powerful field - without having to learn a new language or framework. What You Need: You'll need a macOS, Windows, or Linux distribution with an up-to-date Elixir installation.

Practical Handbook of Genetic Algorithms

Practical Handbook of Genetic Algorithms PDF Author: Lance D. Chambers
Publisher: CRC Press
ISBN: 1420050087
Category : Computers
Languages : en
Pages : 592

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Book Description
Practical Handbook of Genetic Algorithms, Volume 3: Complex Coding Systems contains computer-code examples for the development of genetic algorithm systems - compiling them from an array of practitioners in the field. Each contribution of this singular resource includes: unique code segments documentation descripti

An Introduction to Genetic Algorithms for Scientists and Engineers

An Introduction to Genetic Algorithms for Scientists and Engineers PDF Author: David A. Coley
Publisher: World Scientific
ISBN: 9789810236021
Category : Mathematics
Languages : en
Pages : 248

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Book Description
This invaluable book has been designed to be useful to most practising scientists and engineers, whatever their field and however rusty their mathematics and programming might be. The approach taken is largely practical, with algorithms being presented in full and working code (in BASIC, FORTRAN, PASCAL AND C) included on a floppy disk to help the reader get up and running as quickly as possible. The text could also be used as part of an undergraduate course on search and optimisation. Student exercises are included at the end of several of the chapters, many of which are computer-based and designed to encourage exploration of the method.