{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T21:05:31Z","timestamp":1761599131492,"version":"3.41.2"},"reference-count":43,"publisher":"Emerald","issue":"8","license":[{"start":{"date-parts":[[2014,8,26]],"date-time":"2014-08-26T00:00:00Z","timestamp":1409011200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,8,26]]},"abstract":"<jats:sec>\n               <jats:title content-type=\"abstract-heading\">Purpose<\/jats:title>\n               <jats:p> \u2013 Expert Cloud as a new class of Cloud computing systems enables its users to request the skill, knowledge and expertise of people by employing internet infrastructures and Cloud computing concepts without any information of their location. Job scheduling is one of the most important issue in Expert Cloud and impacts on its efficiency and customer satisfaction. The purpose of this paper is to propose an applicable method based on genetic algorithm for job scheduling in Expert Cloud. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title>\n               <jats:p> \u2013 Because of the nature of the scheduling issue as a NP-Hard problem and the success of genetic algorithm in optimization and NP-Hard problems, the authors used a genetic algorithm to schedule the jobs on human resources in Expert Cloud. In this method, chromosome or candidate solutions are represented by a vector; fitness function is calculated based on response time; one point crossover and swap mutation are also used. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Findings<\/jats:title>\n               <jats:p> \u2013 The results indicate that the proposed method can schedule the received jobs in appropriate time with high accuracy in comparison to common methods (First Come First Served, Shortest Process Next and Highest Response Ratio Next). Also the proposed method has better performance in term of total execution time, service+wait time, failure rate and Human Resource utilization rate in comparison to common methods. <\/jats:p>\n            <\/jats:sec>\n            <jats:sec>\n               <jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title>\n               <jats:p> \u2013 In this paper the job scheduling issue in Expert Cloud is pointed out and the approach to resolve the problem is applied into a practical example.<\/jats:p>\n            <\/jats:sec>","DOI":"10.1108\/k-02-2013-0018","type":"journal-article","created":{"date-parts":[[2014,10,3]],"date-time":"2014-10-03T11:46:53Z","timestamp":1412336813000},"page":"1262-1275","source":"Crossref","is-referenced-by-count":47,"title":["Job scheduling in the Expert Cloud based on genetic algorithms"],"prefix":"10.1108","volume":"43","author":[{"given":"Nima","family":"Jafari Navimipour","sequence":"first","affiliation":[]},{"given":"Amir","family":"Masoud Rahmani","sequence":"additional","affiliation":[]},{"given":"Ahmad","family":"Habibizad Navin","sequence":"additional","affiliation":[]},{"given":"Mehdi","family":"Hosseinzadeh","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020122923401326200_b1","unstructured":"Abdoun, O.\n               , \n                  Tajani, C.\n                and \n                  Abouchabaka, J.\n                (2012), \u201cAnalyzing the performance of mutation operators to solve the traveling salesman problem\u201d, International Journal of Emerging Sciences, Vol. 2 No. 1, pp. 61-77."},{"key":"key2020122923401326200_b2","doi-asserted-by":"crossref","unstructured":"Abrishami, S.\n                and \n                  Naghibzadeh, M.\n                (2012), \u201cDeadline-constrained workflow scheduling in software as a service cloud\u201d, Scientia Iranica, Vol. 19 No. 3, pp. 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