Data-driven distributionally robust chance-constrained optimization with large data set and outliers: Sequential sample removal algorithm for solution improvement-Reference-Cited by-同舟云学术

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Data-driven distributionally robust chance-constrained optimization with large data set and outliers: Sequential sample removal algorithm for solution improvement

Published:2023-11 Issue: Volume:179 Page:108407
ISSN:0098-1354
Container-title:Computers & Chemical Engineering
language:en
Short-container-title:Computers & Chemical Engineering

Author:

Yang Shu-Bo^ORCID,Kammammettu Sanjula,Li Zukui^ORCID

Funder

Natural Sciences and Engineering Research Council of Canada

Publisher

Elsevier BV

Subject

Computer Science Applications,General Chemical Engineering

Reference45 articles.

1. Data-driven individual and joint chance-constrained optimization via kernel smoothing;Calfa;Comput. Chem. Eng.,2015

2. Bayesian nonparametric set construction for robust optimization;Campbell,2015

3. Sinkhorn distances: Lightspeed computation of optimal transport;Cuturi;Adv. Neural Inf. Process. Syst.,2013

4. Optimization of Chemical Processes;Edgar,2001

5. Data-driven distributionally robust optimization using the wasserstein metric: Performance guarantees and tractable reformulations;Esfahani;Appl. Manag. Sci.,2018

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1. Credible joint chance-constrained low-carbon energy Management for Multi-energy Microgrids;Applied Energy;2025-01

2. Novel approach for industrial process anomaly detection based on process mining;Journal of Process Control;2024-04

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