52 citations · 125 across the 7 of their papers we have counts for
7 papers
Vector Autoregressive Evolution for Dynamic Multi-Objective Optimisation
Shouyong Jiang, Yong Wang, Yaru Hu +2
Dynamic multi-objective optimisation (DMO) handles optimisation problems with multiple (often conflicting) objectives in varying environments. Such problems pose various challenges…
Benchmark Functions for CEC 2022 Competition on Seeking Multiple Optima in Dynamic Environments
Wenjian Luo, Xin Lin, Changhe Li +2
Dynamic and multimodal features are two important properties and widely existed in many real-world optimization problems. The former illustrates that the objectives and/or constrai…
Generating Large-scale Dynamic Optimization Problem Instances Using the Generalized Moving Peaks Benchmark
Mohammad Nabi Omidvar, Danial Yazdani, Juergen Branke +3
This document describes the generalized moving peaks benchmark (GMPB) and how it can be used to generate problem instances for continuous large-scale dynamic optimization problems.…
Competition on Dynamic Optimization Problems Generated by Generalized Moving Peaks Benchmark (GMPB)
Danial Yazdani, Michalis Mavrovouniotis, Changhe Li +6
The Generalized Moving Peaks Benchmark (GMPB) is a tool for generating continuous dynamic optimization problem instances with controllable dynamic and morphological characteristics…
A Multiobjective State Transition Algorithm Based on Decomposition
Xiaojun Zhou, Yuan Gao, Shengxiang Yang +2
Aggregation functions largely determine the convergence and diversity performance of multi-objective evolutionary algorithms in decomposition methods. Nevertheless, the traditional…
A Scalable Test Suite for Continuous Dynamic Multiobjective Optimisation
Shouyong Jiang, Marcus Kaiser, Shengxiang Yang +2
Dynamic multiobjective optimisation has gained increasing attention in recent years. Test problems are of great importance in order to facilitate the development of advanced algori…
An Adaptive Framework to Tune the Coordinate Systems in Evolutionary Algorithms
Zhi-Zhong Liu, Yong Wang, Shengxiang Yang +1
In the evolutionary computation research community, the performance of most evolutionary algorithms (EAs) depends strongly on their implemented coordinate system. However, the comm…