Refine
Year of publication
Document Type
- Report (22) (remove)
Has Fulltext
- yes (22)
Keywords
- Optimierung (10)
- Soft Computing (8)
- Modellierung (6)
- Evolutionärer Algorithmus (4)
- Globale Optimierung (4)
- Genetisches Programmieren (3)
- Maschinelles Lernen (3)
- Mehrkriterielle Optimierung (3)
- Metaheuristik (3)
- Optimization (3)
- Sequential Parameter Optimization (3)
- Sequentielle Parameter Optimierung (3)
- Computational Intelligence (2)
- Ensemble Methods (2)
- Evolutionsstrategie (2)
- Genetic Programming (2)
- Genetische Algorithmen (2)
- Multi-Criteria Optimization (2)
- Multiobjective Optimization (2)
- Optimierungsproblem (2)
- Prognose (2)
- Simulation (2)
- Surrogat-Modellierung (2)
- Surrogate Modeling (2)
- Surrogate Models (2)
- Versuchsplanung (2)
- Algorithm Tuning (1)
- Algorithmus (1)
- Automated Learning (1)
- Bayesian Learning (1)
- Bayesian Regression (1)
- Co-Kriging (1)
- Cyber-physische Produktionssysteme (1)
- Cyclone Dust Separator (1)
- Data Analysis (1)
- Data Mining (1)
- Data Modelling (1)
- Datenanalyse (1)
- Ensemble based modeling (1)
- Entstauber (1)
- Event Detection (1)
- Evolution Strategies (1)
- Evolutionary Algorithms (1)
- Evolutionsstrategien (1)
- Evolutionäre Algorithmen (1)
- Expected Improvement (1)
- Experiment (1)
- Experimental Algorithmics (1)
- Fehlende Daten (1)
- Finanzwirtschaft (1)
- Flushing (1)
- Function Approximation (1)
- Gaussian Process (1)
- Genetic Algorithms (1)
- Genetic programming (1)
- Heuristics (1)
- Imputation (1)
- Kognitive Referenzarchitektur (1)
- Kriging (1)
- Lineare Regression (1)
- Machine Learning (1)
- Massive Online Analysis (1)
- Metamodel (1)
- Metamodell (1)
- Missing Data (1)
- Mixed Models (1)
- Model Selection (1)
- Multi-criteria Optimization (1)
- On-line Algorithm (1)
- Parametertuning (1)
- R (1)
- Regression (1)
- SPOT (1)
- Sensortechnik (1)
- Simulated annealing (1)
- Spülen (1)
- Stacked Generalization (1)
- Statistics (1)
- Surrogate (1)
- Surrogate Model (1)
- Surrogate Optimization (1)
- Surrogate-Model-Based Optimization (1)
- Surrogate-model-based Optimization (1)
- Surrogatmodellbasierte Optimierung (1)
- Taxonomie (1)
- Taxonomy (1)
- Time-series (1)
- Trinkwasserversorgung (1)
- Unsicherheit (1)
- Vorverarbeitung (1)
- Wasserwirtschaft (1)
- Water Distribution Systems (1)
- Water Quality Monitoring (1)
- Zeitreihe (1)
- Zeitreihenanalyse (1)
- Zylon Enstauber (1)
There is a strong need for sound statistical analysis of simulation and optimization algorithms. Based on this analysis, improved parameter settings can be determined. This will be referred to as tuning. Model-based investigations are common approaches in simulation and optimization. The sequential parameter optimization toolbox (SPOT), which is implemented as a package for the statistical programming language R, provides sophisticated means for tuning and understanding simulation and optimization algorithms. The toolbox includes methods for tuning based on classical regression and analysis of variance techniques; tree-based models such as classification and regressions trees (CART) and random forest; Gaussian process models (Kriging), and combinations of different meta-modeling approaches. This article exemplifies how an existing optimization algorithm, namely simulated annealing, can be tuned using the SPOT framework.
Multi-criteria optimization has gained increasing attention during the last decades. This article exemplifies multi-criteria features, which are implemented in the statistical software package SPOT. It describes related software packages such as mco and emoa and gives a comprehensive introduction to simple multi criteria optimization tasks. Several hands-on examples are used for illustration. The article is well-suited as a starting point for performing multi-criteria optimization tasks with SPOT.