Synthesis and Design of Processing Networks: Stochastic Formulation and Solution

Alberto Quaglia, Bent Sarup, Gürkan Sin, Rafiqul Gani

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

In this contribution, we propose an integrated business and engineering framework for synthesis and design of processing networks under uncertainty. In our framework, an adapted formulation of the transhipment problem is integrated with a superstructure, leading to a Stochastic Mixed Integer Non Linear Program (sMINLP), which is solved
to determine simultaneously the optimal strategic and tactical decisions with respect to the processing network, the material flows, raw material and product portfolio. The framework allows time-effective and robust formulation, solution and analysis of largescale synthesis problems in presence of uncertainty parameters, contributing to broaden the range of application of stochastic programming and optimization to real industrial problems. The framework is applied to an industrial case study based on soybean processing, to identify the optimal processing network under market and technical uncertainty.
Original languageEnglish
Title of host publicationProceedings of the 22nd European Symposium on Computer Aided Process Engineering
EditorsIan David Lockhart Bogle, Michael Fairweather
PublisherElsevier
Publication date2012
Pages467-471
Publication statusPublished - 2012
Event22nd European Symposium on Computer Aided Process Engineering - London, United Kingdom
Duration: 17 Jun 201222 Jun 2012

Conference

Conference22nd European Symposium on Computer Aided Process Engineering
CountryUnited Kingdom
CityLondon
Period17/06/201222/06/2012
SeriesComputer Aided Chemical Engineering
Volume30
ISSN1570-7946

Keywords

  • Mixed Integer Non Linear Programming (MINLP)
  • Integrated business and engineering decision making

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