dc.creatorVeintimilla Reyes, Jaime Eduardo
dc.date.accessioned2018-01-11T16:47:20Z
dc.date.accessioned2022-10-21T00:54:01Z
dc.date.available2018-01-11T16:47:20Z
dc.date.available2022-10-21T00:54:01Z
dc.date.created2018-01-11T16:47:20Z
dc.date.issued2016-06-01
dc.identifier18777058
dc.identifierhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85004000492&doi=10.1016%2fj.proeng.2016.11.045&partnerID=40&md5=cd64a544d57ed67fa1a0e9ea26be93ce
dc.identifierhttp://dspace.ucuenca.edu.ec/handle/123456789/29077
dc.identifier10.1016/j.proeng.2016.11.045
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4627521
dc.description.abstractWater of sufficient quantity and quality is indispensable for multiple purposes like domestic use, irrigated agriculture, hydropower generation and ecosystem functioning. However, in many regions of the world water availability is limited and even declining. Moreover, water availability is variable in space and time so that it does not match with the spatio-temporal use pattern of the water consumers. To overcome the temporal discrepancy between availability and consumption, reservoirs are constructed. Monitoring and predicting the water available in the reservoirs, the needs of the consumers and the losses throughout the water distribution system are necessary requirements to fairly allocate the available water for the different consumers. In this article, the water allocation problem is considered as a Network Flow Optimization Problem (NFOP) to be solved by a spatio-temporal optimization approach using Mixed Integer Linear Programming (MILP) techniques.
dc.languageen_US
dc.publisherELSEVIER LTD
dc.sourceProcedia Engineering
dc.subjectAllocation
dc.subjectChain
dc.subjectGurobi
dc.subjectOptimization
dc.subjectWater
dc.titleMixed Integer Linear Programming (MILP) Approach to Deal with Spatio-temporal Water Allocation
dc.typeArticle


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