relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3252/
title: Worst Case Scenario Robust Optimization Utilizing Adaptive Dynamic Taylor Kriging and Differential Evolution Algorithm
creator: Xia, Bin
creator: Pham, Minh Trien
creator: Ren, Ziyan Ren
creator: Zhang, Yanli
creator: Koh, Chang Seop
subject: Electronics and Communications
description: For the robust optimal design of electromagnetic problems under uncertainties, the robustness evaluation is the critical problem. This paper presents a surrogate model based worst case scenario optimization algorithm, where the adaptive dynamic Taylor Kriging is incorporated to construct a higher accurate surrogate model. Finally, an improved differential evo- lution algorithm, DE/λ-best/1/bin, is adopted to search for the global robust optimal solution.
date: 2018-10-28
type: Conference or Workshop Item
type: PeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3252/1/3-WC-ADTK_final.pdf
identifier:   Xia, Bin and Pham, Minh Trien and Ren, Ziyan Ren and Zhang, Yanli and Koh, Chang Seop  (2018) Worst Case Scenario Robust Optimization Utilizing Adaptive Dynamic Taylor Kriging and Differential Evolution Algorithm.  In: 2018 IEEE 18th Biennial Conference on Electromagnetic Field Computations (CEFC2018), 28-31 October 2018, Hangzhou, China.     
relation: http://www.cefc2018.org/system/Web/ueditor/asp/upload/file/20181008/15389866299155943.pdf