Kriging Surrogate Based Multi-objective Optimization of Bulk Vinyl Acetate Polymerization with Branching

被引:46
|
作者
Mogilicharla, Anitha [1 ]
Mittal, Prateek [1 ]
Majumdar, Saptarshi [1 ]
Mitra, Kishalay [1 ]
机构
[1] Indian Inst Technol Hyderabad, Dept Chem Engn, Yeddumailaram 502205, Andhra Pradesh, India
关键词
Optimization; Branching; NSGA-II; Multi-objective; Kriging; Pareto; GENETIC ALGORITHMS; MOLECULAR-WEIGHT;
D O I
10.1080/10426914.2014.921709
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Despite the established superiority in finding the global as well as well-spread Pareto optimal (PO) points, the need of more numbers of function evaluations for population based evolutionary optimization techniques leads to a computationally demanding proposal. The case becomes more miserable if the function evaluations are carried out using a first principle based computationally expensive model, making the proposal not fit for online usage of the application. In this work, a Kriging based surrogate model has been proposed to replace a computationally expensive model to save execution time while performing an optimization task. A multi-objective optimization study has been carried out for the bulk vinyl acetate polymerization with long-chain branching using these surrogate as well as expensive models and Kriging PO solutions similar to those found by the first principle models are obtained with a close to 85% savings in function evaluations.
引用
收藏
页码:394 / 402
页数:9
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