R2/D-EGO

This repository contains the Matlab code of R2/D-EGO.

Liang Zhao, Xiaobin Huang, Chao Qian, and Qingfu Zhang. Many-to-Few Decomposition: Linking R2-based and Decomposition-based Multiobjective Efficient Global Optimization Algorithms. IEEE Transactions on Evolutionary Computation, 2024. [Post-print PDF] [PDF]

Usage

Matlab >= 2018a

Quick Start

• The run_R2D_EGO.m provides the basic script to run experiments on ZDT and DTLZ.

Advanced usage

• Download PlatEMO (version >=4.6, Matlab >= 2018a).
• Copy the folders within "Algorithms" into the directory at "PlatEMO/Algorithms/". Next, add all of the subfolders contained within the "PlatEMO" directory to the MATLAB search path.
• In the MATLAB command window, type platemo() to run PlatEMO using the GUI.
• Select the label "expensive" and choose the algorithm "R2D-EGO".
  • Default setting of batch size: 5.
• Select a problem and set appropriate parameters.
  • e.g., ZDT1, N=200, M=2, D=8, maxFE=200.

If you have any questions or feedback, please feel free to contact [email protected] and [email protected].

Citation

If you find our work is helpful to your research, please cite our paper.

Acknowledgements

• This implementation is based on PlatEMO.
• For GP modeling, we leverage the DACE toolbox.