Pflacco: Feature-Based Landscape Analysis of Continuous and Constrained Optimization Problems in Python

Author:

Prager Raphael Patrick1,Trautmann Heike23

Affiliation:

1. Department of Information Systems, University of Münster, Münster, 48149, Germany raphael.prager@uni-muenster.de

2. Department of Information Systems, University of Münster, Münster, 48149, Germany

3. Data Management and Biometrics, University of Twente, Enschede, 7522, Netherlands trautmann@uni-muenster.de

Abstract

Abstract The herein proposed Python package pflacco provides a set of numerical features to characterize single-objective continuous and constrained optimization problems. Thereby, pflacco addresses two major challenges in the area optimization. Firstly, it provides the means to develop an understanding of a given problem instance, which is crucial for designing, selecting, or configuring optimization algorithms in general. Secondly, these numerical features can be utilized in the research streams of automated algorithm selection and configuration. While the majority of these landscape features is already available in the R package flacco, our Python implementation offers these tools to an even wider audience and thereby promotes research interests and novel avenues in the area of optimization.

Publisher

MIT Press

Subject

Computational Mathematics

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1. Analyzing Violation Landscapes Using Different Definitions of Constraint Violation;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2024-07-14

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