Randomized Sketching Algorithms for Low-Memory Dynamic Optimization

2021 ◽  
Vol 31 (2) ◽  
pp. 1242-1275
Author(s):  
Ramchandran Muthukumar ◽  
Drew P. Kouri ◽  
Madeleine Udell
2009 ◽  
Vol 20 (3) ◽  
pp. 608-619 ◽  
Author(s):  
Xiang BAI ◽  
Yu-Ming MAO ◽  
Su-Peng LENG ◽  
Jian-Bing MAO ◽  
Jun XIE

Author(s):  
Aristide Tolok Nelem ◽  
Pierre Ele ◽  
Papa Alioune Ndiaye ◽  
Salomé Ndjakomo Essiane ◽  
Mathieu Jean Pierre Pesdjock

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Ashraf Azmi ◽  
Suhairi Abdul Sata ◽  
Fakhrony Sholahudin Rohman ◽  
Norashid Aziz

AbstractThe highly exothermic nature of the low-density polyethylene (LDPE) polymerization process and the heating-cooling prerequisite in tubular reactor can lead to various problems particularly safety and economic. These issues complicate the monomer conversion maximization approaches. Consequently, the dynamic optimization study to obtain maximum conversion of the LDPE is carried out. A mathematical model has been developed and validated using industrial data. In the dynamic optimization study, maximum monomer conversion (XM) is considered as the objective function, whereas the constraint and bound consists of maximum reaction temperature and product melt flow index (MFI). The orthogonal collocation (OC) on finite elements is used to convert the original optimization problems into Nonlinear Programming (NLP) problems, which are then solved using sequential quadratic program (SQP) methods. The result shows that five interval numbers produce better optimization result compared to one and two intervals.


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