Efficient Decomposition Approach for Large-Scale Refinery Scheduling-Reference-Cited by-同舟云学术

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Efficient Decomposition Approach for Large-Scale Refinery Scheduling

Published:2015-10-13 Issue:41 Volume:54 Page:9964-9991
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Shah Nikisha K.¹,Sahay Nihar¹,Ierapetritou Marianthi G.¹

Affiliation:

1. Chemical and Biochemical Engineering Department, Rutgers University, New Jersey, United States

Funder

Division of Chemical, Bioengineering, Environmental, and Transport Systems

U.S. Department of Education

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ie504835b

Reference47 articles.

1. Refinery Short-Term Scheduling Using Continuous Time Formulation: Crude-Oil Operations

2. Petroleum Refining Operations: Key Issues, Advances, and Opportunities

3. Global Optimal Scheduling of Crude Oil Blending Operations with RTN Continuous-time and Multiparametric Disaggregation

4. Mixed-Integer Linear Programming Model for Refinery Short-Term Scheduling of Crude Oil Unloading with Inventory Management

5. A discretization-based approach for the optimization of the multiperiod blend scheduling problem

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1. A Refinery Production Scheduling Model with Operation Mode Transition Based on Variable Driven Modelling Approach;Journal of Chemical Engineering of Japan;2024-08-06

2. Large-scale optimization of nonconvex MINLP refinery scheduling;Computers & Chemical Engineering;2024-07

3. Blend Scheduling Solutions in Petroleum Refineries towards Automated Decision-Making in Industrial-like Blend-Shops;Processes;2024-03-13

4. Optimal Refinery Crude Oil Scheduling Based on Proximal Policy Optimization;2023 9th International Conference on Computer and Communications (ICCC);2023-12-08

5. A Review: Machine Learning for Combinatorial Optimization Problems in Energy Areas;Algorithms;2022-06-13

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