Test Problems in Optimization

TL;DR

This paper emphasizes the importance of diverse test functions in optimization and provides a curated list of test problems for unconstrained optimization to standardize validation procedures.

Contribution

It introduces a selected set of test problems for unconstrained optimization, addressing the lack of a standard test function list in the literature.

Findings

Highlights the need for diverse test functions in algorithm validation

Provides a curated list of test problems for unconstrained optimization

Aims to standardize testing procedures in optimization research

Abstract

Test functions are important to validate new optimization algorithms and to compare the performance of various algorithms. There are many test functions in the literature, but there is no standard list or set of test functions one has to follow. New optimization algorithms should be tested using at least a subset of functions with diverse properties so as to make sure whether or not the tested algorithm can solve certain type of optimization efficiently. Here we provide a selected list of test problems for unconstrained optimization.