Export Citations
Save this search
Please login to be able to save your searches and receive alerts for new content matching your search criteria.
- surveyJuly 2023
Recent Advances in Bayesian Optimization
ACM Computing Surveys (CSUR), Volume 55, Issue 13sArticle No.: 287, Pages 1–36https://doi.org/10.1145/3582078Bayesian optimization has emerged at the forefront of expensive black-box optimization due to its data efficiency. Recent years have witnessed a proliferation of studies on the development of new Bayesian optimization algorithms and their applications. ...
- research-articleJune 2023
Federated Many-Task Bayesian Optimization
IEEE Transactions on Evolutionary Computation (TEC), Volume 28, Issue 4Pages 980–993https://doi.org/10.1109/TEVC.2023.3279775Bayesian optimization (BO) is a powerful surrogate-assisted algorithm for solving expensive black-box optimization problems. While BO was developed for centralized optimization, the availability of massive distributed data has attracted increased ...
- research-articleSeptember 2021
Transfer learning based surrogate assisted evolutionary bi-objective optimization for objectives with different evaluation times
AbstractVarious multiobjective optimization algorithms have been proposed with a common assumption that the evaluation of each objective function takes the same period of time. Little attention has been paid to more general and realistic ...
- research-articleJune 2020
Transfer learning for gaussian process assisted evolutionary bi-objective optimization for objectives with different evaluation times
GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation ConferencePages 587–594https://doi.org/10.1145/3377930.3390147Despite the success of evolutionary algorithms (EAs) for solving multi-objective problems, most of them are based on the assumption that all objectives can be evaluated within the same period of time. However, in many real-world applications, such an ...
- research-articleMay 2020
An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimization
Information Sciences: an International Journal (ISCI), Volume 519, Issue CPages 317–331https://doi.org/10.1016/j.ins.2020.01.048AbstractSurrogate models have been widely used for solving computationally expensive multi-objective optimization problems (MOPs). The efficient global optimization (EGO) algorithm, a Bayesian approach to surrogate-assisted optimization, has ...
- research-articleJanuary 2016
A statistical atlas based approach to automated subject-specific FE modeling
Computer-Aided Design (CADE), Volume 70, Issue CPages 67–77https://doi.org/10.1016/j.cad.2015.07.003Subject-specific modeling is increasingly important in biomechanics simulation. However, how to automatically create high-quality finite element (FE) mesh and how to automatically impose boundary condition are challenging.This paper presents a ...
- articleJanuary 2014
An optimization approach for constructing trivariate B-spline solids
In this paper, we present an approach that automatically constructs a trivariate tensor-product B-spline solid via a gradient-based optimization approach. Given six boundary B-spline surfaces for a solid, this approach finds the internal control points ...
- ArticleJune 2010
Analyzing Automobile Performance by Powertrain Simulation and Fuzzy Control
ICECE '10: Proceedings of the 2010 International Conference on Electrical and Control EngineeringPages 2667–2670https://doi.org/10.1109/iCECE.2010.1444In order to analyze the dynamic performance and estimate fuel cost of automobile in the city streets, a simulation model of automobile is constructed and examined. Then the driver comfort is optimized by using this model. To better evaluate the driving ...