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Baranwal M, Selukar M, Lotti R, Paranjape AA, Majumder S, Rocher J. A scalable optimization framework for refinery operation and management. Comput Chem Eng 2023. [DOI: 10.1016/j.compchemeng.2023.108242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
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Computational Experience with Piecewise Linear Relaxations for Petroleum Refinery Planning. Processes (Basel) 2021. [DOI: 10.3390/pr9091624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Refinery planning optimization is a challenging problem as regards handling the nonconvex bilinearity, mainly due to pooling operations in processes such as crude oil distillation and product blending. This work investigated the performance of several representative piecewise linear (or piecewise affine) relaxation schemes (referred to as McCormick, bm, nf5, and nf6t) and de (which is a new approach proposed based on eigenvector decomposition) that mainly give rise to mixed-integer optimization programs to convexify a bilinear term using predetermined univariate partitioning for instances of uniform and non-uniform partition sizes. The computational results showed that applying these schemes improves the relaxation tightness compared to only applying convex and concave envelopes as estimators. Uniform partition sizes typically perform better in terms of relaxation solution quality and convergence behavior. It was also seen that there is a limit on the number of partitions that contribute to relaxation tightness, which does not necessarily correspond to a larger number of partitions, while a direct relationship between relaxation size and tightness does not always hold for non-uniform partition sizes.
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Global optimization of large-scale MIQCQPs via cluster decomposition: Application to short-term planning of an integrated refinery-petrochemical complex. Comput Chem Eng 2020. [DOI: 10.1016/j.compchemeng.2020.106883] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Siamizade MR. Global Optimization of Refinery-wide Production Planning with Highly Nonlinear Unit Models. Ind Eng Chem Res 2019. [DOI: 10.1021/acs.iecr.9b00887] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Mahmud R. Siamizade
- School of Chemical, Biological and Materials Engineering, University of Oklahoma, Norman, Oklahoma 73019, United States
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Castillo Castillo P, Castro PM, Mahalec V. Global Optimization Algorithm for Large-Scale Refinery Planning Models with Bilinear Terms. Ind Eng Chem Res 2017. [DOI: 10.1021/acs.iecr.6b01350] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
| | - Pedro M. Castro
- Centro
de Matemática Aplicações Fundamentais e Investigação
Operacional, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Vladimir Mahalec
- Department of Chemical
Engineering, McMaster University, Hamilton, ON L8S 4A7, Canada
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