Pareto Optimization of Low-Density Polyethylene in a Tubular Reactor Using a Hybrid Strategy

被引：2

作者：

Rohman, Fakhrony Sholahudin ^{[1
]}

Zahan, Khairul Azly ^{[2
,3
]}

Muhammad, Dinie ^{[1
]}

Murat, Muhamad Nazri ^{[1
]}

机构：

[1] Univ Sains Malaysia, Sch Chem Engn, Engn Campus, Nibong Tebal 14300, Pulau Pinang, Malaysia

[2] Kyoto Univ, Grad Sch Informat, Dept Syst Sci, Kyoto 6068501, Japan

[3] Univ Tun Hussein Onn Malaysia, Fac Engn Technol, Batu Pahat 86400, Johor, Malaysia

来源：

CHEMICAL ENGINEERING & TECHNOLOGY | 2022年 / 45卷 / 12期

关键词：

Low-density polyethylene; Multi-objective optimization; Pareto optimization; Tubular reactor; GENETIC ALGORITHM; POLYMERIZATION; SIMULATION; ETHYLENE;

D O I：

10.1002/ceat.202200295

中图分类号：

TQ [化学工业];

学科分类号：

0817 ;

摘要：

Multi-objective optimization (MOO) to produce low-density polyethylene (LDPE) in a tubular reactor is performed for three different purposes, namely, maximizing the monomer exchange rate, lowering operational costs, and increasing the productivity. The ASPEN simulator is used to resolve optimization problems. Here, MOO of particle swamp optimization (MOPSO), non-dominated sorting genetic algorithm (NSGA-II), and a hybrid strategy of NSGA II-MOPSO are employed as a model-based optimization for LDPE production in a tubular reactor. The results demonstrated that the hybrid strategy of NSGA II-MOPSO is the most effective MOO strategy. Using the hybrid strategy, the discovered solution set provides the utmost precision and diversity along the Pareto front.

引用

页码：2292 / 2303

页数：12

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