A bi-stage surrogate-assisted hybrid algorithm for expensive optimization problems

Surrogate-Assisted Artificial Immune Systems for Expensive Optimization Problems

A multi-fidelity surrogate-model-assisted evolutionary algorithm for computationally expensive optimization problems

Integrating data-driven surrogate models and simulation models of di erent accuracies (or delities) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple delities in global optimization is a major challenge. To address it, the two major contrib...

Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling

We present a parallel evolutionary optimization algorithm that leverages surrogate models for solving computationally expensive design problems with general constraints, on a limited computational budget. The essential backbone of our framework is an evolutionary algorithm coupled with a feasible sequential quadratic programming solver in the spirit of Lamarckian learning.We employ a trust-regi...

A hybrid one-then-two stage algorithm for computationally expensive electromagnetic design optimization

Purpose – The purpose of this paper is to propose a surrogate model-assisted optimization algorithm which effectively searches for the optimum at the earliest opportunity, avoiding the need for a large initial experimental design, which may be wasteful. Design/methodology/approach – The methodologies of two-stage and one-stage selection of points are combined for the first time. After creating ...

A computational intelligence algorithm for expensive engineering optimization problems

The modern engineering design optimization process often replaces laboratory experiments with computer simulations, which leads to expensive black-box optimization problems. Such problems often contain candidate solutions which cause the simulation to fail, and therefore they will have no objective value assigned to them, a scenario which degrades the search effectiveness. To address this, this...