Learning to guide particle search for dynamic multi-objective optimization

Date

2024-02-23

Advisors

Journal Title

Journal ISSN

ISSN

2168-2275

Volume Title

Publisher

IEEE

Type

Article

Peer reviewed

Yes

Abstract

Dynamic multiobjective optimization problems (DMOPs) are characterized by multiple objectives that change over time in varying environments. More specifically, environmental changes can be described as various dynamics. However, it is difficult for existing dynamic multiobjective algorithms (DMOAs) to handle DMOPs due to their inability to learn in different environments to guide the search. Besides, solving DMOPs is typically an online task, requiring low computational cost of a DMOA. To address the above challenges, we propose a particle search guidance network (PSGN), capable of directing individuals’ search actions, including learning target selection and acceleration coefficient control. PSGN can learn the actions that should be taken in each environment through rewarding or punishing the network by reinforcement learning. Thus, PSGN is capable of tackling DMOPs of various dynamics. Additionally, we efficiently adjust PSGN hidden nodes and update the output weights in an incremental learning way, enabling PSGN to direct particle search at a low computational cost. We compare the proposed PSGN with seven state-of-the-art algorithms, and the excellent performance of PSGN verifies that it can handle DMOPs of various dynamics in a computationally very efficient way.

Description

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.

Keywords

Dynamic multiobjective optimization, incremental learning, neural network, particle swarm optimization, reinforcement learning

Citation

Song, W., Liu, S., Wang, X., Yang, S. and Jin, Y. (2024) Learning to guide particle search for dynamic multi-objective optimization. IEEE Transactions on Cybernetics,

Rights

Attribution-NonCommercial-NoDerivs 2.0 UK: England & Wales
http://creativecommons.org/licenses/by-nc-nd/2.0/uk/

Research Institute

Institute of Artificial Intelligence (IAI)