A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimization
Simulation-based hull form optimization is a typical HEB (high-dimensional, expensive computationally, black-box) problem. Conventional optimization algorithms easily fall into the “curse of dimensionality” when dealing with HEB problems. A recently proposed Cross-Entropy (CE) optimization algorithm...
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doaj-e89ccea9e0e1455399747b4c332506972021-03-09T04:14:02ZengElsevierInternational Journal of Naval Architecture and Ocean Engineering2092-67822021-11-0113115125A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimizationXin Liu0Heng Zhang1Qiang Liu2Suzhen Dong3Changshi Xiao4Weihai Institute of Marine Information Science and Technology, Shandong Jiaotong University, Weihai, 264400, China; Hubei Key Laboratory of Inland Shipping Technology, Wuhan, 430000, ChinaWuchang Shipbuilding Industry Group Co., Ltd., Wuhan, 430000, China; Corresponding author.Wuchang Shipbuilding Industry Group Co., Ltd., Wuhan, 430000, ChinaSOYOTEC LIMITED, Beijing, 100176, ChinaHubei Key Laboratory of Inland Shipping Technology, Wuhan, 430000, ChinaSimulation-based hull form optimization is a typical HEB (high-dimensional, expensive computationally, black-box) problem. Conventional optimization algorithms easily fall into the “curse of dimensionality” when dealing with HEB problems. A recently proposed Cross-Entropy (CE) optimization algorithm is an advanced stochastic optimization algorithm based on a probability model, which has the potential to deal with high-dimensional optimization problems. Currently, the CE algorithm is still in the theoretical research stage and rarely applied to actual engineering optimization. One reason is that the Monte Carlo (MC) method is used to estimate the high-dimensional integrals in parameter update, leading to a large sample size. This paper proposes an improved CE algorithm based on quasi-Monte Carlo (QMC) estimation using high-dimensional truncated Sobol subsequence, referred to as the QMC-CE algorithm. The optimization performance of the proposed algorithm is better than that of the original CE algorithm. With a set of identical control parameters, the tests on six standard test functions and a hull form optimization problem show that the proposed algorithm not only has faster convergence but can also apply to complex simulation optimization problems.http://www.sciencedirect.com/science/article/pii/S2092678221000017Hull form optimizationCross-entropy optimization algorithmQuasi-Monte Carlo estimationSobol sequence |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xin Liu Heng Zhang Qiang Liu Suzhen Dong Changshi Xiao |
spellingShingle |
Xin Liu Heng Zhang Qiang Liu Suzhen Dong Changshi Xiao A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimization International Journal of Naval Architecture and Ocean Engineering Hull form optimization Cross-entropy optimization algorithm Quasi-Monte Carlo estimation Sobol sequence |
author_facet |
Xin Liu Heng Zhang Qiang Liu Suzhen Dong Changshi Xiao |
author_sort |
Xin Liu |
title |
A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimization |
title_short |
A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimization |
title_full |
A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimization |
title_fullStr |
A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimization |
title_full_unstemmed |
A cross-entropy algorithm based on Quasi-Monte Carlo estimation and its application in hull form optimization |
title_sort |
cross-entropy algorithm based on quasi-monte carlo estimation and its application in hull form optimization |
publisher |
Elsevier |
series |
International Journal of Naval Architecture and Ocean Engineering |
issn |
2092-6782 |
publishDate |
2021-11-01 |
description |
Simulation-based hull form optimization is a typical HEB (high-dimensional, expensive computationally, black-box) problem. Conventional optimization algorithms easily fall into the “curse of dimensionality” when dealing with HEB problems. A recently proposed Cross-Entropy (CE) optimization algorithm is an advanced stochastic optimization algorithm based on a probability model, which has the potential to deal with high-dimensional optimization problems. Currently, the CE algorithm is still in the theoretical research stage and rarely applied to actual engineering optimization. One reason is that the Monte Carlo (MC) method is used to estimate the high-dimensional integrals in parameter update, leading to a large sample size. This paper proposes an improved CE algorithm based on quasi-Monte Carlo (QMC) estimation using high-dimensional truncated Sobol subsequence, referred to as the QMC-CE algorithm. The optimization performance of the proposed algorithm is better than that of the original CE algorithm. With a set of identical control parameters, the tests on six standard test functions and a hull form optimization problem show that the proposed algorithm not only has faster convergence but can also apply to complex simulation optimization problems. |
topic |
Hull form optimization Cross-entropy optimization algorithm Quasi-Monte Carlo estimation Sobol sequence |
url |
http://www.sciencedirect.com/science/article/pii/S2092678221000017 |
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