{"id":80,"date":"2019-08-16T20:04:33","date_gmt":"2019-08-16T18:04:33","guid":{"rendered":"https:\/\/ramoths.org:907\/wordpress\/?page_id=80"},"modified":"2019-08-19T15:31:41","modified_gmt":"2019-08-19T13:31:41","slug":"icsde-17","status":"publish","type":"page","link":"https:\/\/mbenabdouallah.com\/index.php\/icsde-17\/","title":{"rendered":"ICSDE &rsquo;17"},"content":{"rendered":"\n<p style=\"text-align:center\" class=\"has-medium-font-size\"><strong>Comparison between GA and ACO for Emergency\nCoverage Problem in a Smart Healthcare Environment <\/strong><strong>&nbsp;<\/strong><\/p>\n\n\n\n<p style=\"text-align:center\">     &nbsp;<strong>Meryam BENABDOUALLAH, Chakib BOJJI<\/strong><\/p>\n\n\n\n<p style=\"text-align:center\"><strong> <\/strong> Industrial Performance Team (PI) ENSET Mohammed V University in   Rabat MOROCCO   <\/p>\n\n\n\n<p>&nbsp;<strong>ABSTRACT <\/strong><\/p>\n\n\n\n<p class=\"txt-justify\">Healthcare management is widely used by researchers\naround the world to strengthen the hospital logistics and improve the patients&rsquo;\nservice. Adopting smart technologies in healthcare environment helps us to\nimprove the quality of care and minimize the waiting time of patients during emergency\ninterventions. Recently, communication technologies such as Internet Of Things,\nCloud Computing and optimization algorithms are emerged. The objective of this\npaper is to compare solutions of the emergency coverage problem done by two\napproaches: Genetic Algorithm \u2018GA\u2019 &amp; Ant Colony Optimization \u2018ACO\u2019. The\ncoverage model aims to minimize the total lateness of ambulances.\nImplementations using GA and ACO are based on random instances during the two\nperiods of the day: day and night. An instance contains hospitals and fire\nstations where ambulances are located and the intervention sectors which are\npatients\u2019 locations. The solution has two parts; the minimal lateness (fitness)\nand the best distribution of the given ambulances in waiting sites (hospitals\n&amp; fire stations). A comparative analysis between GA &amp; ACO is shown. GA\nbrings best solution. <\/p>\n\n\n\n<p><strong>KEYWORDS <\/strong><\/p>\n\n\n\n<p>Emergency, smart, genetic algorithm, ant colony\noptimization, lateness, ambulance, healthcare.<strong><\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Comparison between GA and ACO for Emergency Coverage Problem in a Smart Healthcare Environment &nbsp; &nbsp;Meryam BENABDOUALLAH, Chakib BOJJI Industrial<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"colormag_page_container_layout":"default_layout","colormag_page_sidebar_layout":"default_layout","footnotes":""},"class_list":["post-80","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/mbenabdouallah.com\/index.php\/wp-json\/wp\/v2\/pages\/80","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/mbenabdouallah.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/mbenabdouallah.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/mbenabdouallah.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/mbenabdouallah.com\/index.php\/wp-json\/wp\/v2\/comments?post=80"}],"version-history":[{"count":4,"href":"https:\/\/mbenabdouallah.com\/index.php\/wp-json\/wp\/v2\/pages\/80\/revisions"}],"predecessor-version":[{"id":434,"href":"https:\/\/mbenabdouallah.com\/index.php\/wp-json\/wp\/v2\/pages\/80\/revisions\/434"}],"wp:attachment":[{"href":"https:\/\/mbenabdouallah.com\/index.php\/wp-json\/wp\/v2\/media?parent=80"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}