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Aiming at the task scheduling problem in cloud environment, this paper analyses the scheduling model of cloud tasks, proposed an improved genetic algorithm (PGA) based on phagocytosis, changed the crossover operation of standard genetic algorithm (GA), formed a sub-chromosome individual after phagocytosis of two mother chromosomes, another individual was generated randomly, and the new individual generated after phagocytosis is determined by the fitness function and the load-balancing standard deviation, so that the evolution process can ensure a high proportion of high-quality individuals in the population. Ensure the diversity of the population. Then a multi-population hybrid coevolutionary genetic algorithm (MPHC_GA) is adopted, which uses the Min-Min algorithm to generate initial multiple sub-populations, and these sub-populations are evolved by standard genetic algorithm (GA) and improved genetic algorithm (PGA) based on phagocytosis. The simulation results show that the proposed algorithm is effective in cloud task scheduling.<\/jats:p>","DOI":"10.3233\/jifs-179398","type":"journal-article","created":{"date-parts":[[2019,9,24]],"date-time":"2019-09-24T14:55:09Z","timestamp":1569336909000},"page":"239-246","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":13,"title":["Application research based on improved genetic algorithm in cloud task scheduling"],"prefix":"10.1177","volume":"38","author":[{"given":"Yang","family":"Sun","sequence":"first","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianrong","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xueliang","family":"Fu","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haifang","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Honghui","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer and Information Engineering, Inner Mongolia Agricultural University, Hohhot, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2019,9,23]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.1145\/1364782.1364786"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2015.07.016"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2011.04.007"},{"key":"e_1_3_2_5_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0158229"},{"key":"e_1_3_2_6_2","first-page":"1","article-title":"A genetic algorithmic method for scheduling optimization in cloud computing services","volume":"5","author":"Gawanmeh A.","year":"2017","unstructured":"A.Gawanmeh, S.Parvin and A.Alwadi, A genetic algorithmic method for scheduling optimization in cloud computing services, Arabian Journal for Science & Engineering 5 (2017), 1\u201310.","journal-title":"Arabian Journal for Science & Engineering"},{"key":"e_1_3_2_7_2","doi-asserted-by":"crossref","unstructured":"X.Sheng and Q.Li Template-Based Genetic Algorithm for QoS-Aware Task Scheduling in Cloud Computing International Conference on Advanced Cloud & Big Data IEEE 2016 pp. 25\u201330.","DOI":"10.1109\/CBD.2016.015"},{"key":"e_1_3_2_8_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13673-017-0109-2"},{"key":"e_1_3_2_9_2","first-page":"17","article-title":"Efficient task scheduling multi-objective particle swarm optimization in cloud computing","author":"Alkayal E.S.","year":"2017","unstructured":"E.S.Alkayal, N.R.Jennings and M.F.Abulkhair, Efficient task scheduling multi-objective particle swarm optimization in cloud computing, Local Computer Networks Workshops IEEE (2017), 17\u201324.","journal-title":"Local Computer Networks Workshops IEEE"},{"key":"e_1_3_2_10_2","first-page":"38","article-title":"Study and analysis of task scheduling algorithms in clouds based on artificial bee colony","author":"Hallaj E.","year":"2016","unstructured":"E.Hallaj and S.R.K.Tabbakh, Study and analysis of task scheduling algorithms in clouds based on artificial bee colony, International Congress on Technology IEEE (2016), 38\u201345.","journal-title":"International Congress on Technology IEEE"},{"key":"e_1_3_2_11_2","doi-asserted-by":"crossref","unstructured":"Y.Li et al. 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