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Integrating Graph-based Representation and Genetic Algorithm for Large-Scale Optimization: Refinery Crude Oil Scheduling
Published in Elsevier B.V.
Volume: 29
Pages: 567 - 571
Scheduling optimization problems are often associated with large number of variables and combinatorial constraints. These problems can be represented graphically through a network structure. This graphical representation can provide important insights to handle the combinatorial constraints. In this study, the graphical representation is incorporated in the framework of genetic algorithm to solve large-scale refinery crude oil scheduling problems. Our results show that use of such graphical representation offers significant advantages while solving multi-objective, multi-solution and nonlinear formulations in reasonable computational time. © 2011 Elsevier B.V.
About the journal
JournalData powered by TypesetComputer Aided Chemical Engineering
PublisherData powered by TypesetElsevier B.V.
Open AccessNo