{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T18:23:40Z","timestamp":1770747820141,"version":"3.49.0"},"reference-count":24,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2016,8,5]],"date-time":"2016-08-05T00:00:00Z","timestamp":1470355200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Intelligent &amp; Fuzzy Systems"],"published-print":{"date-parts":[[2017,1,13]]},"abstract":"<jats:p>Flexible flow shop scheduling problems become more complex when uncertain factors are taken into consideration. Most literature are under the assumption that machines are continuous available. But, a machine can be unavailable for many reasons, such as breakdown and planned preventive maintenance. Once a machine breaks down, then the original schedule can not be executed and we must make the corresponding adjustment according to the actual situation. This paper deals with a flexible flow shop scheduling problem with uncertain processing and repair time subject to breakdowns. Machines are non-continuously available, i.e., they break down at arbitrary time instance not known in advance. The problem with breakdowns is modeled as a series of problems without breakdowns. To solve the problem, approaches including genetic algorithm and particle swarm optimization are used in this paper. A numerical example shows the effectiveness of the proposed approach.<\/jats:p>","DOI":"10.3233\/jifs-151400","type":"journal-article","created":{"date-parts":[[2016,8,16]],"date-time":"2016-08-16T14:34:48Z","timestamp":1471358088000},"page":"207-214","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":10,"title":["Uncertain flexible flow shop scheduling problem subject to breakdowns"],"prefix":"10.1177","volume":"32","author":[{"given":"Jiayu","family":"Shen","sequence":"first","affiliation":[{"name":"School of Science, Nanjing University of Science and Technology, Nanjing, Jiangsu, P.R. China"}]},{"given":"Yuanguo","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Science, Nanjing University of Science and Technology, Nanjing, Jiangsu, P.R. 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