{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T16:23:42Z","timestamp":1769185422621,"version":"3.49.0"},"reference-count":46,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T00:00:00Z","timestamp":1643587200000},"content-version":"vor","delay-in-days":30,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61963022"],"award-info":[{"award-number":["61963022"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62173169"],"award-info":[{"award-number":["62173169"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2022,1]]},"abstract":"<jats:p>\n                    This paper considers two kinds of stochastic reentrant job shop scheduling problems (SRJSSP), i.e., the SRJSSP with the maximum tardiness criterion and the SRJSSP with the makespan criterion. Owing to the NP\u2010complete complexity of the considered RJSSPs, an effective differential evolutionary algorithm (DEA) combined with two uncertainty handling techniques, namely, DEA_UHT, is proposed to address these problems. Firstly, to reasonably control the computation cost, the optimal computing budget allocation technique (OCBAT) is applied for allocating limited computation budgets to assure reliable evaluation and identification for excellent solutions or individuals, and the hypothesis test technique (HTT) is added to execute a statistical comparison to reduce some unnecessary repeated evaluation. Secondly, a reentrant\u2010largest\u2010order\u2010value rule is designed to convert the DEA\u2019s individual (i.e., a continuous vector) to the SRJSSP\u2019s solution (i.e., an operation permutation). Thirdly, a conventional active decoding scheme for the job shop scheduling problem is extended to decode the solution for obtaining the criterion value. Fourthly, an\n                    <jats:italic>Insert<\/jats:italic>\n                    \u2010based exploitation strategy and an\n                    <jats:italic>Interchange<\/jats:italic>\n                    \u2010based exploration strategy are devised to enhance DEA\u2019s exploitation ability and exploration ability, respectively. Finally, the test results and comparisons manifest the effectiveness and robustness of the proposed DEA_UHT.\n                  <\/jats:p>","DOI":"10.1155\/2022\/9924163","type":"journal-article","created":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T22:20:08Z","timestamp":1643667608000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Differential Evolution Algorithm Combined with Uncertainty Handling Techniques for Stochastic Reentrant Job Shop Scheduling Problem"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5000-6625","authenticated-orcid":false,"given":"Rong","family":"Hu","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6514-2056","authenticated-orcid":false,"given":"Xing","family":"Wu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0048-1487","authenticated-orcid":false,"given":"Bin","family":"Qian","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1407-4863","authenticated-orcid":false,"given":"Jianlin","family":"Mao","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2627-431X","authenticated-orcid":false,"given":"Huaiping","family":"Jin","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2022,1,31]]},"reference":[{"key":"e_1_2_10_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2010.03.013"},{"key":"e_1_2_10_2_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-004-2296-z"},{"key":"e_1_2_10_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-00142-0_26"},{"key":"e_1_2_10_4_2","doi-asserted-by":"publisher","DOI":"10.1287\/moor.1.2.117"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2003.10.004"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00170-008-1881-y"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-09339-0_69"},{"key":"e_1_2_10_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/0925-5273(95)00078-8"},{"key":"e_1_2_10_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jmaa.2008.12.065"},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cor.2009.07.002"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2011.06.001"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2011.09.050"},{"key":"e_1_2_10_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2011.11.018"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-38527-8_35"},{"key":"e_1_2_10_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2013.09.246"},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/619254"},{"key":"e_1_2_10_17_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cirpj.2015.03.003"},{"key":"e_1_2_10_18_2","doi-asserted-by":"crossref","unstructured":"Kemmoe-TchomteS. 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