dc.contributor.author | Puleo, V | |
dc.contributor.author | Morley, MS | |
dc.contributor.author | Freni, G | |
dc.contributor.author | Savic, D | |
dc.date.accessioned | 2016-05-04T15:17:21Z | |
dc.date.issued | 2014 | |
dc.description.abstract | Linear, 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.citation | HIC 2014 - 11th International Conference on Hydroinformatics, 2014-08-17, 2014-08-21, New York City, USA | en_GB |
dc.identifier.uri | http://hdl.handle.net/10871/21380 | |
dc.language.iso | en | en_GB |
dc.publisher | CUNY Academic Works | en_GB |
dc.relation.url | http://academicworks.cuny.edu/cc_conf_hic/156 | en_GB |
dc.title | A Hybrid optimization method for real-time pump scheduling | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2016-05-04T15:17:21Z | |
dc.description | Session S6-02, Special Session: Evolutionary Computing in Water Resources Planning and Management II | en_GB |