Multi-Objective evolutionary algorithm for modeling of site suitability for health-care facilities

dc.contributor.author	Beheshtifar, Sara	en
dc.contributor.author	Alimohammadi, Abbas	el
dc.date.accessioned	2014-07-18T22:54:08Z
dc.date.available	2014-07-18T22:54:08Z
dc.date.issued	2014-07-19
dc.identifier.uri	http://hdl.handle.net/11400/1410
dc.rights	Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ηνωμένες Πολιτείες	*
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/3.0/us/	*
dc.source	www.hsj.gr	en
dc.subject	Geographic information systems
dc.subject	Multi-objective optimization
dc.subject	Evolutionary algorithms
dc.subject	Location modeling
dc.title	Multi-Objective evolutionary algorithm for modeling of site suitability for health-care facilities	en
heal.type	journalArticle
heal.generalDescription	Research article	en
heal.classification	Medicine
heal.classification	Science Mathematics
heal.classification	Ιατρική
heal.classification	Μαθηματικά
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh00006614
heal.classificationURI	http://id.loc.gov/authorities/subjects/sh2010112231
heal.classificationURI	N/A-Ιατρική
heal.classificationURI	N/A-Μαθηματικά
heal.keywordURI	http://id.loc.gov/authorities/subjects/sh90001880
heal.language	en
heal.access	free
heal.recordProvider	Τεχνολογικό Εκπαιδευτικό Ίδρυμα Αθήνας.Σχολή Επαγγελμάτων Υγείας και Πρόνοιας. Τμήμα Νοσηλευτικής	el
heal.publicationDate	2013-05
heal.bibliographicCitation	Beheshtifar, S. & Alimohammadi, A. (June 2013) Multi-Objective evolutionary algorithm for modeling of site suitability for health-care facilities. “Health Science Journal”. 7(2). p. 209-217.	en
heal.abstract	Introduction: To meet ever-increasing demands for health-care services, it is necessary to determine optimal locations for new health-care facilities. Method: A multi-objective model based on the genetic algorithm (GA) has been applied to evaluate site suitability for new clinics in part of Tehran urban areas. A multi-objective GA has been combined with a single GA to solve the location-allocation problem composed of the three objective functions. Geo-spatial Information System (GIS) has been used to prepare, analyze and visualize spatial data. Results: The results showed that optimizing of a single objective may result in unacceptable solutions with respect to other objectives. For example, the best solution resulting from optimization of the second objective function (proximity of the sites to the streets), was the worst one according to the first (travel cost) and third (land-use compatibility) objective functions. Therefore, 10 alternative solutions as the Pareto front in the objective area were indentified and investigated. Conclusion: Visualization of the best solutions for each objective and compromise between different objectives provide valuable possibilities for selection of the best alternative for decision makers.	en
heal.publisher	Μαρβάκη, Χριστίνα	el
heal.journalName	Health Science Journal	en
heal.journalType	peer-reviewed
heal.fullTextAvailability	true
heal.dateCreated	2013-04