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

Raphael Patrick Prager, Heike Trautmann

Research output: Contribution to journalArticleAcademicpeer-review

10 Citations (Scopus)

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 of 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 are 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.

Original languageEnglish
Pages (from-to)211-216
Number of pages6
JournalEvolutionary Computation
Volume32
Issue number3
DOIs
Publication statusPublished - 3 Sept 2024

Keywords

  • NLA

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