| Vorliegende Sprache |
eng |
| Hinweise auf parallele Ausgaben |
392964171 Druckausg.: ‡EVOLVE - a bridge between probability, set oriented numerics, and evolutionary computation ; 4: International Conference, held at Leiden University, July 10 - 13, 2013 |
| ISBN |
978-3-319-01127-1 |
| Name |
Emmerich, Michael |
| Deutz, Andre |
| Name ANZEIGE DER KETTE |
Deutz, Andre |
| Name |
Schütze, Oliver |
| Bäck, Thomas |
| Tantar, Emilia |
| Tantar, Alexandru-Adrian |
| Moral, Pierre Del |
| Legrand, Pierrick |
| Bouvry, Pascal |
| Coello, Carlos A. |
| T I T E L |
EVOLVE - A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation IV |
| Zusatz zum Titel |
International Conference held at Leiden University, July 10-13, 2013 |
| Verlagsort |
Heidelberg |
| Verlag |
Springer |
| Erscheinungsjahr |
2013 |
| 2013 |
| Umfang |
Online-Ressource (XIV, 324 p. 140 illus, digital) |
| Reihe |
Advances in Intelligent Systems and Computing ; 227 |
| Notiz / Fußnoten |
Description based upon print version of record |
| Weiterer Inhalt |
Preface; Organization; Contents; Machine Learning and Probabilistic Models; Complex Networks and Evolutionary Computation; Diversity Oriented Optimization; Set-Oriented Numerics and Evolutionary MultiobjectiveOptimization; Genetic Programming; Constructing a Solution Attractor for the Probabilistic Traveling Salesman Problem through Simulation; 1 Introduction; 2 Monte Carlo Sampling Approximation; 3 Solution Attractor Construction; 4 The Proposed Simulation-Based Search System; 4.1 The Parallel Search System; 4.2 The Experimental Problem; 4.3 The Experiments; 5 Conclusion; References. Training Multilayer Perceptron by Conformal Geometric Evolutionary Algorithm1 Introduction; 2 Geometric Preliminaries; 2.1 Geometric Algebra; 2.2 Conformal Geometric Algebra; 2.3 Inversion on a Hyper-sphere; 3 Conformal Geometric Optimization Algorithm; 4 Implementation; 5 Experimental Setup; 6 Experimental Results; 7 Conclusions; References; RotaSVM: A New Ensemble Classifier; 1 Introduction; 2 Brief Description of Support Vector Machine; 3 ProposedRotaSVM; 4 Empirical Results; 4.1 Data Sets; 4.2 Experimental Setup; 4.3 Results; 5 Conclusions; References. Finding Biologically Plausible Complex Network Topologies with a New Evolutionary Approach for Network Generation1 Introduction; 2 Networks; 2.1 Topological Features; 2.2 Network Models; 3 An Evolutionary Algorithm for the SN model; 3.1 Individuals; 3.2 Mutation and Crossover; 3.3 Parallel Evaluation of Individuals; 3.4 Sorting the Population; 3.5 Fitness Function; 3.6 Hardware and Software Setup; 4 Results; 4.1 E. coli; 4.2 S. cerevisiae; 4.3 MRSA; 5 Discussion; References; Fitness Landscape Analysis of NK Landscapes and Vehicle Routing Problems by Expanded; 1 Introduction. 2 Barrier Trees and Related Work3 Expanded Barrier Trees; 4 Studies on NK Landscapes; 5 Studies on Vehicle Routing Problems; 6 Summary and Outlook; References; Sewer Network Design Optimization Problem Using Ant Colony Optimization Algorithm and Tree Growing Algorithm; 1 Introduction; 2 Sewer Network Design Problem; 3 Ant Colony Optimization Algorithm (ACOA); 4 Tree Growing Algorithm (TGA); 5 Proposed ACOA-TGA for Layout and Size Optimization of Sewer Network; 6 Results of Test Examples and Discussions; 7 Concluding Remarks; References; An Ant-Based Optimization Approach for Inventory Routing. 1 Introduction2 Problem Formulation; 3 Proposed Approach; 3.1 Ant Colony Optimization; 3.2 Solution Representation; 3.3 Algorithm Operators and Procedures; 3.4 Penalty Function; 4 Experimental Results; 5 Conclusions; References; Measuring Multimodal Optimization Solution Sets with a View to Multiobjective Techniques; 1 Introduction; 2 WhatDoWeWant?; 3 Quality Indicators; 3.1 Indicators without Problem Knowledge; 3.2 Indicators Requiring Knowledge of the Optima; 3.3 Indicators Requiring Knowledge of the Basins; 3.4 Extending and Comparing Indicators; 4 Subset Selection Heuristics. 4.1 Nearest Better Clustering (NBC) |
| Titelhinweis |
Druckausg.: ‡EVOLVE - a bridge between probability, set oriented numerics, and evolutionary computation ; 4: International Conference, held at Leiden University, July 10 - 13, 2013 |
| ISBN |
ISBN 978-3-319-01128-8 |
| Klassifikation |
UYQ |
| COM004000 |
| *68-06 |
| 65-06 |
| 90-06 |
| 65Y99 |
| 68T20 |
| 90C29 |
| 90C59 |
| 00B25 |
| 006.3 |
| Q342 |
| Kurzbeschreibung |
Numerical and computational methods are nowadays used in a wide range of contexts in complex systems research, biology, physics, and engineering. Over the last decades different methodological schools have emerged with emphasis on different aspects of computation, such as nature-inspired algorithms, set oriented numerics, probabilistic systems and Monte Carlo methods. Due to the use of different terminologies and emphasis on different aspects of algorithmic performance there is a strong need for a more integrated view and opportunities for cross-fertilization across particular disciplines. These proceedings feature 20 original publications from distinguished authors in the cross-section of computational sciences, such as machine learning algorithms and probabilistic models, complex networks and fitness landscape analysis, set oriented numerics and cell mapping, evolutionary multiobjective optimization, diversity-oriented search, and the foundations of genetic programming algorithms. By presenting cutting edge results with a strong focus on foundations and integration aspects this work presents a stepping stone towards efficient, reliable, and well-analyzed methods for complex systems management and analysis |
| SWB-Titel-Idn |
386844844 |
| Signatur |
Springer E-Book |
| Bemerkungen |
Elektronischer Volltext - Campuslizenz |
| Elektronische Adresse |
$uhttp://dx.doi.org/10.1007/978-3-319-01128-8 |
| Internetseite / Link |
Volltext |
| Siehe auch |
Volltext |
| Siehe auch |
Cover |
| Siehe auch |
Inhaltstext |
