A multi-objective process optimization procedure under uncertainty for sustainable process design

Li Sun, JiPing Pan, Anqi Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Sustainable chemical process design can be formulated as a multi-objective optimization (MOO) problem covering economic, environmental and societal aspects. Moreover, uncertainties are unavoidable during the process design. So, uncertainties should be involved in the optimization. In this work, authors work on the basis of stochastic programming to deal with uncertainty factors, and integrate MOO deterministic algorithms to identify the optimal process design for the improvement of sustainability from a number of alternatives. The efficacy of the procedure is demonstrated by design of 1-hexene separation process.
Original languageEnglish
Title of host publication2008 2nd International Conference on Bioinformatics and Biomedical Engineering
PublisherIEEE
Pages4373-4376
Number of pages4
ISBN (Print)9781424417476
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 2nd International Conference on Bioinformatics and Biomedical Engineering - Shanghai , China
Duration: 16 May 200818 May 2008

Conference

Conference2008 2nd International Conference on Bioinformatics and Biomedical Engineering
CountryChina
CityShanghai
Period16/05/0818/05/08

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  • Cite this

    Sun, L., Pan, J., & Wang, A. (2008). A multi-objective process optimization procedure under uncertainty for sustainable process design. In 2008 2nd International Conference on Bioinformatics and Biomedical Engineering (pp. 4373-4376). IEEE. https://doi.org/10.1109/ICBBE.2008.591