Kaisa Miettinen / Marko M. Mäkelä / Pekka Neittaanmäki / Jacques Périaux (Hgg.)Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming, and Industrial Applications
Evolutionary Algorithms in Engineering and Computer Science
Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming, and Industrial Applications
Herausgegeben:Miettinen, Kaisa; Mäkelä, Marko M.; Neittaanmäki, Pekka; Périaux, Jacques
Kaisa Miettinen / Marko M. Mäkelä / Pekka Neittaanmäki / Jacques Périaux (Hgg.)Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming, and Industrial Applications
Evolutionary Algorithms in Engineering and Computer Science
Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming, and Industrial Applications
Herausgegeben:Miettinen, Kaisa; Mäkelä, Marko M.; Neittaanmäki, Pekka; Périaux, Jacques
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Evolutionäre Algorithmen sind Methoden künstlicher Intelligenz, die die Natur imitieren und für ihre Robustheit bei der Durchsuchung großer Räume und bei der Auffindung von Optima nahe des globalen Optimums bekannt sind. Dieser Band enthält die Vortragsmanuskripte des dritten EUROGEN-Kurses (Jyväskylä, Finnland, Mai/Juni 1999), in dessen Mittelpunkt die Anwendung des evolutionären Computings auf reale Probleme der Ingenieurtechnik steht. Genetic algorithms (GA) and evolution strategies (ES) are relatively new stochastic based techniques for solving engineering problems on computers. GA and ES…mehr
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Evolutionäre Algorithmen sind Methoden künstlicher Intelligenz, die die Natur imitieren und für ihre Robustheit bei der Durchsuchung großer Räume und bei der Auffindung von Optima nahe des globalen Optimums bekannt sind. Dieser Band enthält die Vortragsmanuskripte des dritten EUROGEN-Kurses (Jyväskylä, Finnland, Mai/Juni 1999), in dessen Mittelpunkt die Anwendung des evolutionären Computings auf reale Probleme der Ingenieurtechnik steht. 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).
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Produktdetails
- Produktdetails
- Verlag: Wiley & Sons
- 1. Auflage
- Seitenzahl: 500
- Erscheinungstermin: 9. Juli 1999
- Englisch
- Abmessung: 240mm x 161mm x 31mm
- Gewicht: 968g
- ISBN-13: 9780471999027
- ISBN-10: 0471999024
- Artikelnr.: 09411324
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: Wiley & Sons
- 1. Auflage
- Seitenzahl: 500
- Erscheinungstermin: 9. Juli 1999
- Englisch
- Abmessung: 240mm x 161mm x 31mm
- Gewicht: 968g
- ISBN-13: 9780471999027
- ISBN-10: 0471999024
- Artikelnr.: 09411324
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
K. Miettinen is the editor of Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming and Industrial Applications, published by Wiley. Pekka Neittaanmäki is the editor of Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming and Industrial Applications, published by Wiley. M. M. Mäkelä is the editor of Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming and Industrial Applications, published by Wiley. Jacques Périaux is the editor of Evolutionary Algorithms in Engineering and Computer Science: Recent Advances in Genetic Algorithms, Evolution Strategies, Evolutionary Programming, Genetic Programming and Industrial Applications, published by Wiley.
METHODOLOGICAL ASPECTS.
Using Genetic Algorithms for Optimization: Technology Transfer in Action
(J. Haataja).
An Introduction to Evolutionary Computation and Some Applications (D.
Fogel).
Evolutionary Computation: Recent Developments and Open Issues (K. De Jong).
Some Recent Important Foundational Results in Evolutionary Computation (D.
Fogel). Evolutionary Algorithms for Engineering Applications (Z.
Michalewicz, et al.).
Embedded Path Tracing and Neighbourhood Search Techniques (C. Reeves T.
Yamada). Parallel and Distributed Evolutionary Algorithms (M. Tomassini).
Evolutionary Multi-Criterion Optimization (K. Deb).
ACO Algorithms for the Traveling Salesman Problem (T. Stützle M. Dorigo).
Genetic Programming: Turing's Third Way to Achieve Machine Intelligence (J.
Koza, et al.).
Automatic Synthesis of the Topology and Sizing for Analog Electrical
Circuits Using Genetic Programming (F. Bennett, et al.).
APPLICATION-ORIENTED APPROACHES.
Multidisciplinary Hybrid Constrained GA Optimization (G. Dulikravich, et
al.).
Genetic Algorithm as a Tool for Solving Electrical Engineering Problems (M.
Rudnicki, et al.).
Genetic Algorithms in Shape Optimization: Finite and Boundary Element
Applications (M. Cerrolaza W. Annicchiarico).
Genetic Algorithms and Fractals (E. Lutton).
Three Evolutionary Approaches to Clustering (H. Luchian).
INDUSTRIAL APPLICATIONS.
Evolutionary Algorithms Applied to Academic and Industrial Test Cases (T.
Bäck, et al.).
Optimization of an Active Noise Control System Inside an Aircraft, Based on
the Simultaneous Optimal Positioning of Microphones and Speakers, with the
Use of a Genetic Algorithm (Z. Diamantis, et al.).
Generator Scheduling in Power Systems by Genetic Algorithm and Expert
System (B. Galvan, et al.).
Efficient Partitioning Methods for 3-D Unstructured Grids Using Genetic
Algorithms (A. Giotis, et al.).
Genetic Algorithms in Shape Optimization of a Paper Machine Headbox (J.
Hämäläinen, et al.).
A Parallel Genetic Algorithm for Multi-Objective Optimization in
Computational Fluid Dynamics (N. Marco, et al.).
Application of a Multi Objective Genetic Algorithm and a Neural Network to
the Optimisation of Foundry Processes (G. Meneghetti, et al.).
Circuit Partitioning Using Evolution Algorithms (J. Montiel-Nelson, et al.
).
Using Genetic Algorithms for Optimization: Technology Transfer in Action
(J. Haataja).
An Introduction to Evolutionary Computation and Some Applications (D.
Fogel).
Evolutionary Computation: Recent Developments and Open Issues (K. De Jong).
Some Recent Important Foundational Results in Evolutionary Computation (D.
Fogel). Evolutionary Algorithms for Engineering Applications (Z.
Michalewicz, et al.).
Embedded Path Tracing and Neighbourhood Search Techniques (C. Reeves T.
Yamada). Parallel and Distributed Evolutionary Algorithms (M. Tomassini).
Evolutionary Multi-Criterion Optimization (K. Deb).
ACO Algorithms for the Traveling Salesman Problem (T. Stützle M. Dorigo).
Genetic Programming: Turing's Third Way to Achieve Machine Intelligence (J.
Koza, et al.).
Automatic Synthesis of the Topology and Sizing for Analog Electrical
Circuits Using Genetic Programming (F. Bennett, et al.).
APPLICATION-ORIENTED APPROACHES.
Multidisciplinary Hybrid Constrained GA Optimization (G. Dulikravich, et
al.).
Genetic Algorithm as a Tool for Solving Electrical Engineering Problems (M.
Rudnicki, et al.).
Genetic Algorithms in Shape Optimization: Finite and Boundary Element
Applications (M. Cerrolaza W. Annicchiarico).
Genetic Algorithms and Fractals (E. Lutton).
Three Evolutionary Approaches to Clustering (H. Luchian).
INDUSTRIAL APPLICATIONS.
Evolutionary Algorithms Applied to Academic and Industrial Test Cases (T.
Bäck, et al.).
Optimization of an Active Noise Control System Inside an Aircraft, Based on
the Simultaneous Optimal Positioning of Microphones and Speakers, with the
Use of a Genetic Algorithm (Z. Diamantis, et al.).
Generator Scheduling in Power Systems by Genetic Algorithm and Expert
System (B. Galvan, et al.).
Efficient Partitioning Methods for 3-D Unstructured Grids Using Genetic
Algorithms (A. Giotis, et al.).
Genetic Algorithms in Shape Optimization of a Paper Machine Headbox (J.
Hämäläinen, et al.).
A Parallel Genetic Algorithm for Multi-Objective Optimization in
Computational Fluid Dynamics (N. Marco, et al.).
Application of a Multi Objective Genetic Algorithm and a Neural Network to
the Optimisation of Foundry Processes (G. Meneghetti, et al.).
Circuit Partitioning Using Evolution Algorithms (J. Montiel-Nelson, et al.
).
METHODOLOGICAL ASPECTS.
Using Genetic Algorithms for Optimization: Technology Transfer in Action
(J. Haataja).
An Introduction to Evolutionary Computation and Some Applications (D.
Fogel).
Evolutionary Computation: Recent Developments and Open Issues (K. De Jong).
Some Recent Important Foundational Results in Evolutionary Computation (D.
Fogel). Evolutionary Algorithms for Engineering Applications (Z.
Michalewicz, et al.).
Embedded Path Tracing and Neighbourhood Search Techniques (C. Reeves T.
Yamada). Parallel and Distributed Evolutionary Algorithms (M. Tomassini).
Evolutionary Multi-Criterion Optimization (K. Deb).
ACO Algorithms for the Traveling Salesman Problem (T. Stützle M. Dorigo).
Genetic Programming: Turing's Third Way to Achieve Machine Intelligence (J.
Koza, et al.).
Automatic Synthesis of the Topology and Sizing for Analog Electrical
Circuits Using Genetic Programming (F. Bennett, et al.).
APPLICATION-ORIENTED APPROACHES.
Multidisciplinary Hybrid Constrained GA Optimization (G. Dulikravich, et
al.).
Genetic Algorithm as a Tool for Solving Electrical Engineering Problems (M.
Rudnicki, et al.).
Genetic Algorithms in Shape Optimization: Finite and Boundary Element
Applications (M. Cerrolaza W. Annicchiarico).
Genetic Algorithms and Fractals (E. Lutton).
Three Evolutionary Approaches to Clustering (H. Luchian).
INDUSTRIAL APPLICATIONS.
Evolutionary Algorithms Applied to Academic and Industrial Test Cases (T.
Bäck, et al.).
Optimization of an Active Noise Control System Inside an Aircraft, Based on
the Simultaneous Optimal Positioning of Microphones and Speakers, with the
Use of a Genetic Algorithm (Z. Diamantis, et al.).
Generator Scheduling in Power Systems by Genetic Algorithm and Expert
System (B. Galvan, et al.).
Efficient Partitioning Methods for 3-D Unstructured Grids Using Genetic
Algorithms (A. Giotis, et al.).
Genetic Algorithms in Shape Optimization of a Paper Machine Headbox (J.
Hämäläinen, et al.).
A Parallel Genetic Algorithm for Multi-Objective Optimization in
Computational Fluid Dynamics (N. Marco, et al.).
Application of a Multi Objective Genetic Algorithm and a Neural Network to
the Optimisation of Foundry Processes (G. Meneghetti, et al.).
Circuit Partitioning Using Evolution Algorithms (J. Montiel-Nelson, et al.
).
Using Genetic Algorithms for Optimization: Technology Transfer in Action
(J. Haataja).
An Introduction to Evolutionary Computation and Some Applications (D.
Fogel).
Evolutionary Computation: Recent Developments and Open Issues (K. De Jong).
Some Recent Important Foundational Results in Evolutionary Computation (D.
Fogel). Evolutionary Algorithms for Engineering Applications (Z.
Michalewicz, et al.).
Embedded Path Tracing and Neighbourhood Search Techniques (C. Reeves T.
Yamada). Parallel and Distributed Evolutionary Algorithms (M. Tomassini).
Evolutionary Multi-Criterion Optimization (K. Deb).
ACO Algorithms for the Traveling Salesman Problem (T. Stützle M. Dorigo).
Genetic Programming: Turing's Third Way to Achieve Machine Intelligence (J.
Koza, et al.).
Automatic Synthesis of the Topology and Sizing for Analog Electrical
Circuits Using Genetic Programming (F. Bennett, et al.).
APPLICATION-ORIENTED APPROACHES.
Multidisciplinary Hybrid Constrained GA Optimization (G. Dulikravich, et
al.).
Genetic Algorithm as a Tool for Solving Electrical Engineering Problems (M.
Rudnicki, et al.).
Genetic Algorithms in Shape Optimization: Finite and Boundary Element
Applications (M. Cerrolaza W. Annicchiarico).
Genetic Algorithms and Fractals (E. Lutton).
Three Evolutionary Approaches to Clustering (H. Luchian).
INDUSTRIAL APPLICATIONS.
Evolutionary Algorithms Applied to Academic and Industrial Test Cases (T.
Bäck, et al.).
Optimization of an Active Noise Control System Inside an Aircraft, Based on
the Simultaneous Optimal Positioning of Microphones and Speakers, with the
Use of a Genetic Algorithm (Z. Diamantis, et al.).
Generator Scheduling in Power Systems by Genetic Algorithm and Expert
System (B. Galvan, et al.).
Efficient Partitioning Methods for 3-D Unstructured Grids Using Genetic
Algorithms (A. Giotis, et al.).
Genetic Algorithms in Shape Optimization of a Paper Machine Headbox (J.
Hämäläinen, et al.).
A Parallel Genetic Algorithm for Multi-Objective Optimization in
Computational Fluid Dynamics (N. Marco, et al.).
Application of a Multi Objective Genetic Algorithm and a Neural Network to
the Optimisation of Foundry Processes (G. Meneghetti, et al.).
Circuit Partitioning Using Evolution Algorithms (J. Montiel-Nelson, et al.
).