Expensive optimization problem (EOP) widely exists in various significant real-world
applications. However, EOP requires expensive or even unaffordable costs for evaluating …

In this paper, an adaptive surrogate-assisted MOEA/D framework (ASA-MOEA/D) is
proposed for solving computationally expensive constrained multi-objective optimization …

The hypervolume metric is widely used to guide the search in multiobjective optimization.
However, in parallel expensive multiobjective optimization, the hypervolume-based …

摘要复杂机电系统设计自动化是知识自动化的一个重要分支, 在机器人系统设计,
高档数控机床设计, 智能装备系统设计等方面具有重要的研究意义和应用价值 …

Variable-fidelity surrogate-based efficient global optimization (EGO) method with the ability
to adaptively select low-fidelity (LF) and high-fidelity (HF) infill point has emerged as an …

Over the past decade, surrogate-assisted evolutionary algorithms have demonstrated their
effectiveness across various computationally expensive real-world domains. Nevertheless …

Many domination-based multi-objective evolutionary algorithms (MOEAs) are designed for
constrained multi-objective optimization problems (CMOPs). However, they still face the …

This paper proposes a distribution information-based Kriging-assisted evolutionary
algorithm (named DISK) to tackle expensive many-objective optimization problems …

This paper proposes a new parameterless constraint-handling technique, named
constrained probabilistic Pareto dominance (CPPD), for expensive constrained …

Expensive multi-objective optimization problems (MOPs) have seen the successful
applications of surrogate-assisted evolutionary algorithms (SAEAs). Nevertheless, the …