{"id":{"repo_id":"utc","oai_identifier":"oai:scholar.utc.edu:theses-1972"},"canonical_url":"https://search.dev.ndltd.org/etd/utc/oai:scholar.utc.edu:theses-1972","repository":{"repo_id":"utc","name":"University of Tennessee - Chattanooga","base_url":"https://scholar.utc.edu/do/oai/"},"display":{"title":"Covering problem with minimum radius enclosing circle","abstract":"This study extends the classical smallest enclosing circle problem in location science to optimize healthcare communication hubs. Given a set of demand points and potential groups, we identify the optimal number of subgroups to cover all points and the circle enclosing them with minimum radius. The center of this circle serves as the communication hub location, minimizing the distance between demand points and facilities subject to customer demand. We develop a nonconvex-nonlinear optimization model and propose a quadratic programming-based approximation algorithm to solve it. Tested on various hypothetical and real scenarios, our model effectively reduces the facility setup cost and identifies the optimal communication hub location.","abstract_html":"This study extends the classical smallest enclosing circle problem in location science to optimize healthcare communication hubs. Given a set of demand points and potential groups, we identify the optimal number of subgroups to cover all points and the circle enclosing them with minimum radius. The center of this circle serves as the communication hub location, minimizing the distance between demand points and facilities subject to customer demand. We develop a nonconvex-nonlinear optimization model and propose a quadratic programming-based approximation algorithm to solve it. 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S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."]},{"key":"dc:description.abstract","label":"Abstract","values":["This study extends the classical smallest enclosing circle problem in location science to optimize healthcare communication hubs. Given a set of demand points and potential groups, we identify the optimal number of subgroups to cover all points and the circle enclosing them with minimum radius. The center of this circle serves as the communication hub location, minimizing the distance between demand points and facilities subject to customer demand. We develop a nonconvex-nonlinear optimization model and propose a quadratic programming-based approximation algorithm to solve it. Tested on various hypothetical and real scenarios, our model effectively reduces the facility setup cost and identifies the optimal communication hub location."]},{"key":"dc:title","label":"Title","values":["Covering problem with minimum radius enclosing circle"]}]}],"canonical_facts":{"dc:contributor":["Weerasena, Lakmali","Aniekan, Ebiefung; Gao, Lani; Bandara, Damitha","College of Arts and Sciences"],"dc:creator":["Onyame, Eric Nartey"],"dc:date":["2023-05-01T07:00:00Z"],"dc:description":["Dept. of Mathematics","M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science."],"dc:description.abstract":["This study extends the classical smallest enclosing circle problem in location science to optimize healthcare communication hubs. Given a set of demand points and potential groups, we identify the optimal number of subgroups to cover all points and the circle enclosing them with minimum radius. The center of this circle serves as the communication hub location, minimizing the distance between demand points and facilities subject to customer demand. We develop a nonconvex-nonlinear optimization model and propose a quadratic programming-based approximation algorithm to solve it. 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