Kaisa Miettinen / Marko M. Mäkelä / Pekka Neittaanmäki / Jacques Périaux (Hgg.)
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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Kaisa Miettinen / Marko M. Mäkelä / Pekka Neittaanmäki / Jacques Périaux (Hgg.)
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
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).
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
- 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
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.).
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.).
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.).