Multi-objective Optimization of Low Density Polyethylene (LDPE) Tubular Reactor Using Strategies of Differential Evolution

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

Multi-objective optimization of industrial low density polyethylene (LDPE) tubular reactor is carried out using improved strategies of multi-objective differential evolution (MODE) algorithm (namely, MODE-III and hybrid-MODE). Two case studies consisting of two-objective optimization and four-objective optimization are considered. In case-1, two objectives namely, maximization of conversion and minimization of the sum of square of normalized side chain concentrations are considered. A set of eleven decision variables, which consists of operating variables, namely, inlet temperature (Tin), inlet pressure (P in), the feed flow rates of -oxygen (Fo), -solvent (FS),-initiators (FI,1, FI,2), and the five average jacket temperatures (TJ,1-TJ,5), are considered. Constraints on maximum temperature attained in the reactor and number average molecular weight are considered. The results of present study show that MODE-III algorithm is able to give consistent results for various control parameters. These results show the ability of the existing algorithm to produce more valuable and practical results that are important to the process plant engineer.

Original languageEnglish
Title of host publicationHandbook of Optimization: From Classical to Modern Approach
Pages615-639
Number of pages25
Volume38
DOIs
Publication statusPublished - 2013

Publication series

NameIntelligent Systems Reference Library
Volume38
ISSN (Print)18684394
ISSN (Electronic)18684408

ASJC Scopus subject areas

  • Computer Science(all)
  • Information Systems and Management
  • Library and Information Sciences

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    Gujarathi, A. M., & Babu, B. V. (2013). Multi-objective Optimization of Low Density Polyethylene (LDPE) Tubular Reactor Using Strategies of Differential Evolution. In Handbook of Optimization: From Classical to Modern Approach (Vol. 38, pp. 615-639). (Intelligent Systems Reference Library; Vol. 38). https://doi.org/10.1007/978-3-642-30504-7_25