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For: Castillo-Castillo PA, Mahalec V. Improved continuous-time model for gasoline blend scheduling. Comput Chem Eng 2016. [DOI: 10.1016/j.compchemeng.2015.08.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Number Cited by Other Article(s)
1
Long J, Deng K, He R. Closed-loop scheduling optimization strategy based on particle swarm optimization with niche technology and soft sensor method of attributes-applied to gasoline blending process. Chin J Chem Eng 2023. [DOI: 10.1016/j.cjche.2023.02.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
2
Wang C, Zhong W, He R, Peng X, Zhao L. A Scenario-Based Chance-Constrained Program for Gasoline Blending under Uncertainty. Ind Eng Chem Res 2022. [DOI: 10.1021/acs.iecr.1c04736] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
3
Castro PM, Grossmann IE, Zhang Q. Expanding scope and computational challenges in process scheduling. Comput Chem Eng 2018. [DOI: 10.1016/j.compchemeng.2018.01.020] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
4
Dimas D, Murata VV, Neiro SMS. A novel transition identification mechanism for the diesel blending and distribution scheduling problem using the discrete time representation with two time-scales granularity. BRAZILIAN JOURNAL OF CHEMICAL ENGINEERING 2017. [DOI: 10.1590/0104-6632.20170344s20150748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
5
Castro PM. Source-based discrete and continuous-time formulations for the crude oil pooling problem. Comput Chem Eng 2016. [DOI: 10.1016/j.compchemeng.2016.06.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
6
Cerdá J, Pautasso PC, Cafaro DC. Optimizing Gasoline Recipes and Blending Operations Using Nonlinear Blend Models. Ind Eng Chem Res 2016. [DOI: 10.1021/acs.iecr.6b01566] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
7
A cost-effective model for the gasoline blend optimization problem. AIChE J 2016. [DOI: 10.1002/aic.15208] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
8
Li J, Xiao X, Floudas CA. Integrated gasoline blending and order delivery operations: Part I. short-term scheduling and global optimization for single and multi-period operations. AIChE J 2016. [DOI: 10.1002/aic.15168] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
9
Castillo-Castillo PA, Mahalec V. Inventory pinch gasoline blend scheduling algorithm combining discrete- and continuous-time models. Comput Chem Eng 2016. [DOI: 10.1016/j.compchemeng.2015.08.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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