Combining Kernelized Autoencoding and Centroid Prediction for Dynamic Multi-objective Optimization

no code implementations • 2 Dec 2023 • Zhanglu Hou, Juan Zou, Gan Ruan, YuAn Liu, Yizhang Xia

Evolutionary algorithms face significant challenges when dealing with dynamic multi-objective optimization because Pareto optimal solutions and/or Pareto optimal fronts change.

Evolutionary Algorithms

Knowledge Transfer for Dynamic Multi-objective Optimization with a Changing Number of Objectives

no code implementations • 19 Jun 2023 • Gan Ruan, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao

Different from most other dynamic multi-objective optimization problems (DMOPs), DMOPs with a changing number of objectives usually result in expansion or contraction of the Pareto front or Pareto set manifold.

Transfer Learning

Evolutionary Optimization for Proactive and Dynamic Computing Resource Allocation in Open Radio Access Network

no code implementations • 12 Jan 2022 • Gan Ruan, Leandro L. Minku, Zhao Xu, Xin Yao

However, the existing problem formulation to solve this resource allocation problem is unsuitable as it defines the capacity utility of resource in an inappropriate way and tends to cause much delay.