| Description |
1 online resource (xxvii, 761 pages) : illustrations |
| Series |
Advances in natural computation ; v. 1 |
|
Advances in natural computation ; v. 1.
|
| Contents |
An Introduction to Multi-Objective Evolutionary Algorithms and Their Applications -- Applications of Multi-Objective Evolutionary Algorithms in Engineering Design -- Optimal Design of Industrial Electromagnetic Devices: A Multiobjective Evolutionary Approach -- Groundwater Monitoring Design: A Case Study Combining Epsilon Dominance Archiving and Automatic Parameterization for the NSGA-II -- Using a Particle Swarm Optimizer with a Multi-Objective Selection Scheme to Design Combinational Logic Circuits -- Application of Multi-Objective Evolutionary Algorithms in Autonomous Vehicles Navigation -- Automatic Control System Design via a Multiobjective Evolutionary Algorithm -- The Use of Evolutionary Algorithms to Solve Practical Problems in Polymer Extrusion -- The Use of Evolutionary Algorithms to Solve Practical Problems in Polymer Extrusion -- City and Regional Planning via a MOEA: Lessons Learned -- A Multi-Objective Evolutionary Algorithm for the Covering Tour Problem -- A Computer Engineering Benchmark Application for Multiobjective Optimizers -- Multiobjective Aerodynamic Design and Visualization of Supersonic Wings by Using Adaptive Range Multiobjective Genetic Algorithms -- Applications of a Multi-Objective Genetic Algorithm in Chemical and Environmental Engineering -- Multi-Objective Spectroscopic Data Analysis of Inertial Confinement Fusion Implosion Cores: Plasma Gradient Determination -- Application of Multiobjective Evolutionary Optimization Algorithms in Medicine -- On Machine Learning with Multiobjective Genetic Optimization -- Generalized Analysis of Promoters: A Method for DNA Sequence Description -- Multi-Objective Evolutionary Algorithms for Computer Science Applications -- Design of Fluid Power System Using a Multi Objective Genetic Algorithm -- Elimination of Exceptional Elements in Cellular Manufacturing Systems Using Multi-Objective Genetic Algorithms -- Single-Objective and Multi-Objective Evolutionary Flowshop Scheduling -- Evolutionary Operators Based on Elite Solutions for Bi-Objective Combinatorial Optimization -- Multi-Objective Rectangular Packing Problem -- Multi-Objective Algorithms for Attribute Selection in Data Mining -- Financial Applications of Multi-Objective Evolutionary Algorithms: Recent Developments and Future Research Directions -- Evolutionary Multi-Objective Optimization Approach to Constructing Neural Network Ensembles for Regression -- Optimizing Forecast Model Complexity Using Multi-Objective Evolutionary Algorithms -- Even Flow Scheduling Problems in Forest Management -- Using Diversity to Guide the Search in Multi-Objective Optimization |
| Summary |
This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain |
| Bibliography |
Includes bibliographical references and index |
| Notes |
English |
|
Print version record |
| Subject |
Combinatorial optimization.
|
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Evolutionary computation.
|
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MATHEMATICS -- Group Theory.
|
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Combinatorial optimization
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Evolutionary computation
|
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Genetische algoritmen.
|
| Form |
Electronic book
|
| Author |
Coello Coello, Carlos A
|
|
Lamont, Gary B
|
| ISBN |
9812567798 |
|
9789812567796 |
|
9812561064 |
|
9789812561060 |
|
1281880841 |
|
9781281880840 |
|
9786611880842 |
|
6611880844 |
|
