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Title: Efficient sampling algorithm for large-scale optimization under uncertainty problems

Abstract

Not provided.

Authors:
; ORCiD logo
Publication Date:
Research Org.:
Univ. of Illinois at Urbana-Champaign, IL (United States)
Sponsoring Org.:
USDOE Office of Fossil Energy (FE)
OSTI Identifier:
1538175
DOE Contract Number:  
FE0011227
Resource Type:
Journal Article
Journal Name:
Computers and Chemical Engineering
Additional Journal Information:
Journal Volume: 115; Journal Issue: C; Journal ID: ISSN 0098-1354
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
Computer Science; Engineering

Citation Formats

Dige, Nishant, and Diwekar, Urmila. Efficient sampling algorithm for large-scale optimization under uncertainty problems. United States: N. p., 2018. Web. doi:10.1016/j.compchemeng.2018.05.007.
Dige, Nishant, & Diwekar, Urmila. Efficient sampling algorithm for large-scale optimization under uncertainty problems. United States. doi:10.1016/j.compchemeng.2018.05.007.
Dige, Nishant, and Diwekar, Urmila. Sun . "Efficient sampling algorithm for large-scale optimization under uncertainty problems". United States. doi:10.1016/j.compchemeng.2018.05.007.
@article{osti_1538175,
title = {Efficient sampling algorithm for large-scale optimization under uncertainty problems},
author = {Dige, Nishant and Diwekar, Urmila},
abstractNote = {Not provided.},
doi = {10.1016/j.compchemeng.2018.05.007},
journal = {Computers and Chemical Engineering},
issn = {0098-1354},
number = C,
volume = 115,
place = {United States},
year = {2018},
month = {7}
}