Sinopsis
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.
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