An on-line variable-fidelity surrogate-assisted harmony search algorithm with multi-level screening strategy for expensive engineering design optimization

This paper presents an on-line variable-fidelity surrogate-assisted harmony search algorithm (VFS-HS) for expensive engineering design optimization problems. VFS-HS employs a novel model-management strategy that uses a multi-level screening mechanism based on non-dominated sorting to strictly control the numbers of low-fidelity and high-fidelity evaluations and to keep a balance between exploration and exploitation. The performance of VFS-HS is validated through comparison not only to those of four single-fidelity surrogate-assisted optimization methods (i.e. the particle swarm optimization algorithm with radial basis function-based surrogate (OPHS-RBF), the two-layer surrogate-assisted particle swarm optimization algorithm (TLSAPSO), the surrogate-assisted hierarchical particle swarm optimization (SH-PSO) and the hybrid surrogate-based optimization using space reduction (HSOSR)) but also to that a multi-fidelity surrogate-assisted optimization method (the multi-fidelity Gaussian process and radial basis function-model-assisted memetic differential evolution (MGPMDE)) on the CEC2014 expensive optimization test suite. A real-world problem of the optimal design for a long cylindrical gas-pressure vessel is also investigated. The results show that VFS-HS outperforms all the compared methods. (C) 2019 Elsevier B.V. All rights reserved.