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dc.contributor.authorPuleo, V
dc.contributor.authorMorley, MS
dc.contributor.authorFreni, G
dc.contributor.authorSavic, D
dc.date.accessioned2016-05-04T15:17:21Z
dc.date.issued2014
dc.description.abstractLinear, non-linear and dynamic programming, heuristics and evolutionary computation are amongst the techniques which have been applied to obtain solutions to optimal pump-scheduling problems. Most of these either greatly simplify the complex water distribution system or require significant time to solve the problem. The scheduling of pumps is frequently undertaken in near-real time, in order to minimize cost and maximize energy savings. However, this requires a computationally efficient algorithm that can rapidly identify an acceptable solution. In this paper, a hybrid optimization model is presented, coupling Linear Programming and Genetic Algorithms. The resulting hybrid optimization model has demonstrated more rapid convergence with respect to the traditional metaheuristic algorithms, whilst maintaining a good level of reliability.en_GB
dc.identifier.citationHIC 2014 - 11th International Conference on Hydroinformatics, 2014-08-17, 2014-08-21, New York City, USAen_GB
dc.identifier.urihttp://hdl.handle.net/10871/21380
dc.language.isoenen_GB
dc.publisherCUNY Academic Worksen_GB
dc.relation.urlhttp://academicworks.cuny.edu/cc_conf_hic/156en_GB
dc.titleA Hybrid optimization method for real-time pump schedulingen_GB
dc.typeConference paperen_GB
dc.date.available2016-05-04T15:17:21Z
dc.descriptionSession S6-02, Special Session: Evolutionary Computing in Water Resources Planning and Management IIen_GB


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