Large-scale Multi-objective Natural Computation Based on Dimensionality Reduction and Clustering

Authors

Weidong Ji, 1.College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China;Follow
Yuqi Yue, 1.College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China;
Xu Wang, 1.College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, China;
Ping Lin, 2.Harbin Medical Sciences University, Harbin 150081, China;

Abstract

Abstract: In multi-objective optimization problems, as the number of decision variables increases, the optimization ability decreases significantly. To solve "dimension disaster", a large-scale multi-objective natural computation method based on dimensionality reduction and clustering is proposed. The decision variables are optimized by locally linear embedding(LLE) to obtain the representation of high-dimensional variables in the low-dimensional space, then the individuals are grouped through K-means to select the appropriate guide individuals for the population to strengthen the convergence and diversity. To verify the effectiveness, the method is applied to the multi-objective particle swarm optimization algorithm and the non-dominated sorting genetic algorithm. The convergence is analyzed to prove that the algorithm converges with probability 1. Experiments is carried out through 8 functions of ZDT and DTLZ series, compared with 6 representative algorithms, and its comprehensive performance is verified through the evaluation results of PF, IGD and HV, and applied to the water pump scheduling problem. Comprehensive experimental results show that the proposed method has better performance.

Recommended Citation

Ji, Weidong; Yue, Yuqi; Wang, Xu; and Lin, Ping (2023) "Large-scale Multi-objective Natural Computation Based on Dimensionality Reduction and Clustering," Journal of System Simulation: Vol. 35: Iss. 1, Article 4.
DOI: 10.16182/j.issn1004731x.joss.21-0667
Available at: https://dc-china-simulation.researchcommons.org/journal/vol35/iss1/4

First Page

41

Revised Date

2021-10-20

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-0667

Last Page

56

CLC

TP391.9

Recommended Citation

Weidong Ji, Yuqi Yue, Xu Wang, Ping Lin. Large-scale Multi-objective Natural Computation Based on Dimensionality Reduction and Clustering[J]. Journal of System Simulation, 2023, 35(1): 41-56.

DOI

10.16182/j.issn1004731x.joss.21-0667