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dc.titleMulti-objective optimization of industrial styrene production using a process simulator and a genetic algorithm
dc.contributor.authorBhutani, N.
dc.contributor.authorTarafder, A.
dc.contributor.authorRay, A.K.
dc.contributor.authorRangaiah, G.P.
dc.identifier.citationBhutani, N.,Tarafder, A.,Ray, A.K.,Rangaiah, G.P. (2004). Multi-objective optimization of industrial styrene production using a process simulator and a genetic algorithm. AIChE Annual Meeting, Conference Proceedings : 7335-7346. ScholarBank@NUS Repository.
dc.description.abstractOptimization of the whole plant instead of important individual units is essential for maximizing savings and operational efficiency. Often, there are conflicting objectives for optimizing industrial processes. Many previous studies on multi-objective optimization involved a few critical units (and not complete plants) using models and simulation programs specifically developed for the respective application. Developing rigorous models and a separate code for simulating a complete plant, for the sake of multi-objective optimization is difficult and time consuming. There is potential to make this task easier by employing available process simulators such as Aspen Plus and Hysys. But these simulators do not currently have multi-objective optimization tools. Hence, an interface has been developed between Non-dominated Sorted Genetic Algorithm (NSGA-II) and Hysys. Plant-wide optimization using this interface involves three main steps: (a) development and testing of Hysys model for steady simulation of the process under study; (b) sensitivity analysis and selection of objectives, decision variables and constraints; and (c) optimization of the process for multiple objectives using NSGA-II. This paper describes optimization of a styrene unit/plant for multiple objectives using the interface and compares the obtained results with those obtained using an independently developed simulation program.
dc.subjectGenetic algorithms
dc.subjectMulti-objective optimization
dc.subjectPlant-wide optimization
dc.typeConference Paper
dc.description.sourcetitleAIChE Annual Meeting, Conference Proceedings
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