Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Comprehensive Feature-Based Landscape Analysis of Continuous and
  Constrained Optimization Problems Using the R-Package flacco   Choosing the best-performing optimizer(s) out of a portfolio of optimization
algorithms is usually a difficult and complex task. It gets even worse, if the
underlying functions are unknown, i.e., so-called Black-Box problems, and
function evaluations are considered to be expensive. In the case of continuous
single-objective optimization problems, Exploratory Landscape Analysis (ELA) -
a sophisticated and effective approach for characterizing the landscapes of
such problems by means of numerical values before actually performing the
optimization task itself - is advantageous. Unfortunately, until now it has
been quite complicated to compute multiple ELA features simultaneously, as the
corresponding code has been - if at all - spread across multiple platforms or
at least across several packages within these platforms.
  This article presents a broad summary of existing ELA approaches and
introduces flacco, an R-package for feature-based landscape analysis of
continuous and constrained optimization problems. Although its functions
neither solve the optimization problem itself nor the related "Algorithm
Selection Problem (ASP)", it offers easy access to an essential ingredient of
the ASP by providing a wide collection of ELA features on a single platform -
even within a single package. In addition, flacco provides multiple
visualization techniques, which enhance the understanding of some of these
numerical features, and thereby make certain landscape properties more
comprehensible. On top of that, we will introduce the package's build-in, as
well as web-hosted and hence platform-independent, graphical user interface
(GUI), which facilitates the usage of the package - especially for people who
are not familiar with R - making it a very convenient toolbox when working
towards algorithm selection of continuous single-objective optimization
problems.

27
The categories of this paper are: comp-gas
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
29
The categories of this paper are: funct-an
10
The categories of this paper are: q-bio
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The categories of this paper are: econ
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The categories of this paper are: chao-dyn
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The categories of this paper are: q-alg
34
The categories of this paper are: chem-ph