A generalised likelihood uncertainty estimation mixed-integer programming model: Application to a water resource distribution network

Autor:	Brian Jones, Godfrey Chagwiza, Senelani D. Hove-Musekwa, Sobona Mtisi
Jazyk:	angličtina
Rok vydání:	2015
Předmět:	Mathematical optimization Distribution (number theory) uncertainty modelling lcsh:Mathematics Resource distribution allocation problem Solver water resources lcsh:QA1-939 Water resources General Energy Uncertainty estimation Model application GLUE Integer programming Mathematics
Zdroj:	Cogent Mathematics, Vol 2, Iss 1 (2015)
ISSN:	2331-1835
Popis:	A framework for incorporating uncertainty in water distribution models that uses generalised likelihood unbiased estimation (GLUE) and mixed-integer programming (MIP) is proposed and applied to a small water distribution system. Model parameters with uncertainty are first modelled in GLUEWIN and the mean estimates are used instead of single-point estimates. The MIP is solved in GAMS using CPlex solver with single-point estimates and then GLUE-generated estimates. There is a large difference between the results from GLUEMIP and those of the general MIP. It is therefore recommended that GLUEMIP framework be used so as to avoid penalties associated with failure to meet demand and for better planning.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::63273e18fe37957a385658c98996d2c3 https://doaj.org/article/e0d7e25c42144f3bb558054f7978281d Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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