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A Novel Parallel Adaptive Survivor Selection Framework for Large-Scale Simulation Optimization

Description:

For stochastic simulation optimization in a modern computing era, we introduce a new parallel framework for solving very large-scale problems using a ranking & selection (R&S) approach that simulates all systems or feasible solutions to provide a global statistical guarantee. We propose a parallel adaptive survivor selection (PASS) framework that...

Keyword:

master-worker, simulation, parallel, stochastic, large-scale, and optimization

Subject:

Applied mathematics, Statistics, and Operations research

Creator:

Pei, Linda

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

06/22/2022

Date Created:

2022-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_903888 and http://dissertations.umi.com/northwestern:16108
Combining Finite Element with Data Analytical Approaches for Structure-Property Modeling in Polymer Nanocomposites

Description:

Polymer nanocomposites have attracted great interest in recent years because of their potential as tailored materials with enhanced properties. Recent experiments have shown that polymer nanocomposites are able to achieve significant improvement in dielectrical, thermal, mechanical and other physical properties compared with their parent polymer systems. More importantly, these outstanding...

Keyword:

polymer nanocomposite, simulation, machine learning, optimization, database, and data mining

Subject:

Mechanical engineering

Creator:

Wang, Yixing

Owner:

Scholarly Digital Publishing

Language:

en

Date Uploaded:

02/12/2020

Date Created:

2019-01-01

Resource Type:

Dissertation

Alternate Identifier:

etdadmin_upload_685582 and http://dissertations.umi.com/northwestern:14811

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A Novel Parallel Adaptive Survivor Selection Framework for Large-Scale Simulation Optimization

Combining Finite Element with Data Analytical Approaches for Structure-Property Modeling in Polymer Nanocomposites

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