Experimental Methods for the Analysis of Optimization Algorithms
In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, comp...
| Συγγραφή απο Οργανισμό/Αρχή: | |
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| Άλλοι συγγραφείς: | , , , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2010.
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Overview
- The Future of Experimental Research
- Design and Analysis of Computational Experiments: Overview
- The Generation of Experimental Data for Computational Testing in Optimization
- The Attainment-Function Approach to Stochastic Multiobjective Optimizer Assessment and Comparison
- Algorithm Engineering: Concepts and Practice
- Characterizing Algorithm Performance
- Algorithm Survival Analysis
- On Applications of Extreme Value Theory in Optimization
- Exploratory Analysis of Stochastic Local Search Algorithms in Biobjective Optimization
- Algorithm Configuration and Tuning
- Mixed Models for the Analysis of Optimization Algorithms
- Tuning an Algorithm Using Design of Experiments
- Using Entropy for Parameter Analysis of Evolutionary Algorithms
- F-Race and Iterated F-Race: An Overview
- The Sequential Parameter Optimization Toolbox
- Sequential Model-Based Parameter Optimization: an Experimental Investigation of Automated and Interactive Approaches.
