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A Two-Level Model Management-Based Surrogate-Assisted Evolutionary Algorithm for Medium-Scale Expensive Multiobjective Optimization

Yuanchao Liu,Jinliang Ding,Qian Li,Fei Li,Jianchang Liu

Published 2025 in IEEE Transactions on Systems, Man, and Cybernetics: Systems

ABSTRACT

Medium-scale expensive multiobjective optimization problems (EMOPs) present a significant challenge to most existing surrogate-assisted evolutionary algorithms (SAEAs). Because the algorithms must balance convergence and diversity with a limited number of fitness evaluations (FEs), while managing the uncertainty in surrogate predictions within the medium-scale decision space. Therefore, this work proposes a surrogate-assisted multiobjective evolutionary algorithm based on two-level model management (SAMOEA-TL2M) to effectively address medium-scale EMOPs. In SAMOEA-TL2M, infill solutions are selected using the proposed two-level model management strategy. In the first level, the estimated non-dominated solutions with good shift-based density estimation (SDE) values are selected for the balance of convergence and diversity. In the second level, the estimated non-dominated solutions and high uncertainty solutions are considered. To quantify uncertainty, an inverse distance weighting (IDW) is introduced. Moreover, an accuracy rate indicator (ARI) is proposed for the optimization state assessment, providing guidance for adaptively executing the two model management levels. Extensive experiments on three widely used instances and time-varying ratio error estimation (TREE) problems with up to 120 dimensions demonstrate the superiority of SAMOEA-TL2M over five state-of-the-art SAEAs in solving medium-scale EMOPs.

PUBLICATION RECORD

  • Publication year

    2025

  • Venue

    IEEE Transactions on Systems, Man, and Cybernetics: Systems

  • Publication date

    2025-11-01

  • Fields of study

    Computer Science, Engineering

  • Identifiers
    DOI 10.1109/TSMC.2025.3604949
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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