Competition on Dynamic Optimization Problems Generated by Generalized Moving Peaks Benchmark (GMPB)
Abstract
The Generalized Moving Peaks Benchmark (GMPB) is a tool for generating continuous dynamic optimization problem instances with controllable dynamic and morphological characteristics. GMPB has been used in recent Competitions on Dynamic Optimization at prestigious conferences, such as the IEEE Congress on Evolutionary Computation (CEC). This dynamic benchmark generator can create a wide variety of landscapes, ranging from simple unimodal to highly complex multimodal configurations and from symmetric to asymmetric forms. It also supports diverse surface textures, from smooth to highly irregular, and can generate varying levels of variable interaction and conditioning. This document provides an overview of GMPB, emphasizing how its parameters can be adjusted to produce landscapes with customizable characteristics. The MATLAB implementation of GMPB is available on the EDOLAB Platform.
Cite
@article{arxiv.2106.06174,
title = {Competition on Dynamic Optimization Problems Generated by Generalized Moving Peaks Benchmark (GMPB)},
author = {Danial Yazdani and Michalis Mavrovouniotis and Changhe Li and Guoyu Chen and Wenjian Luo and Mohammad Nabi Omidvar and Juergen Branke and Shengxiang Yang and Xin Yao},
journal= {arXiv preprint arXiv:2106.06174},
year = {2024}
}
Comments
This is the support document for CEC competition on Dynamic Optimization Problems