Oct 23, 2018 · In this paper, we investigate data-driven evolutionary dynamic optimization. First, we develop a surrogate-assisted evolutionary framework for ...

A surrogate-assisted evolutionary framework for solving data-driven dynamic optimization problems (DD-DOPs) is developed and a benchmark is employed based ...

In this paper, we investigate data-driven evolutionary dynamic optimization. First, we develop a surrogate-assisted evo- lutionary framework for solving data- ...

In this paper, we investigate data-driven evolutionary dynamic optimization. First, we develop a surrogate-assisted evolutionary framework for solving data- ...

Nov 5, 2022 · This paper proposes a simple but effective transfer learning framework to empower data-driven evolutionary optimization to solve dynamic optimization problems.

This study aimed to dynamically provide an optimal surrogate for EA by developing a brand-new SAEA framework.

This approach leverages restricted Boltzmann machines (RBMs) for feature learning and reinforcement learning for adaptive strategy selection.

The Session on Surrogate-Assisted Evolutionary Optimisation (SAEO) aims to promote the research on surrogate-assisted evolutionary optimisation.

Aug 3, 2023 · Data-driven efficient surrogate-assisted evolutionary method for multi-objective optimization of high-dimensional neural dynamical systems.

Dec 1, 2023 · We propose a knowledge-transfer-based method for offline data-driven evolutionary optimization in dynamic environments, where knowledge transfer ...