Ten New Benchmarks for Optimization

TL;DR

This paper introduces ten new optimization benchmarks with diverse properties like noise and discontinuity to better evaluate optimization algorithms.

Contribution

It presents ten novel benchmarks with varied characteristics, expanding the tools available for testing optimization methods.

Findings

New benchmarks include noisy and discontinuous functions.

They facilitate testing of optimization algorithms under diverse conditions.

Enhance evaluation of optimization performance across different scenarios.

Abstract

Benchmarks are used for testing new optimization algorithms and their variants to evaluate their performance. Most existing benchmarks are smooth functions. This chapter introduces ten new benchmarks with different properties, including noise, discontinuity, parameter estimation and unknown paths.