基于广义移动峰值基准（GMPB）生成的动态优化问题竞赛
Competition on Dynamic Optimization Problems Generated by Generalized Moving Peaks Benchmark (GMPB)
AI总结：
本文介绍了可生成可控特征连续动态优化问题的广义移动峰值基准GMPB，说明其多样景观生成能力与参数调节方法，并指出其MATLAB版本已在EDOLAB平台发布。
摘要：
广义移动峰值基准（GMPB）是一种用于生成连续动态优化问题实例的工具，其动态特性与形态特征具备可控性。GMPB已应用于近年在知名会议上举办的动态优化竞赛中，例如IEEE进化计算大会（CEC）。该动态基准生成器可创建种类丰富的适应度景观，涵盖从简单单峰到高度复杂多峰的配置，以及从对称到非对称的形态。它还支持多样的表面纹理，从平滑到高度不规则均可实现，并能生成不同程度的变量交互与条件作用。本文档对GMPB进行了概述，重点说明如何调整其参数以生成具备可定制特征的景观。GMPB的MATLAB实现版本已在EDOLAB平台上线。
英文摘要：
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.
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