{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T17:01:42Z","timestamp":1757610102136,"version":"3.44.0"},"reference-count":27,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2024,3,30]],"date-time":"2024-03-30T00:00:00Z","timestamp":1711756800000},"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: Applications in Engineering and Technology"],"published-print":{"date-parts":[[2025,8]]},"abstract":"<jats:p>Enterprises have increasingly focused on integrated production and transportation problems, recognizing their potential to enhance cohesion across different decision-making levels. The whale optimization algorithm, with its advantages such as minimal parameter control, has garnered attention. In this study, a hybrid whale optimization algorithm (HWOA) is designed to settle the distributed no-wait flow-shop scheduling problem with batch delivery (DNWFSP-BD). Two objectives are considered concurrently, namely, the minimization of the makespan and total energy consumption. In the proposed algorithm, four vectors are proposed to represent a solution, encompassing job scheduling, factory assignment, batch delivery and speed levels. Subsequently, to generate high-quality candidate solutions, a heuristic leveraging the Largest Processing Time (LPT) rule and the NEH heuristic is introduced. Moreover, a novel path-relinking strategy is proposed for a more meticulous search of the optimal solution neighborhood. Furthermore, an insert-reversed block operator and variable neighborhood descent (VND) are introduced to prevent candidate solutions from converging to local optima. Finally, through comprehensive comparisons with efficient algorithms, the superior performance of the HWOA algorithm in solving the DNWFSP-BD is conclusively demonstrated.<\/jats:p>","DOI":"10.3233\/jifs-238627","type":"journal-article","created":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T13:59:44Z","timestamp":1712066384000},"page":"366-379","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["A hybrid whale optimization algorithm for distributed no-wait flow-shop scheduling problem with batch delivery"],"prefix":"10.1177","volume":"49","author":[{"given":"Xin-jie","family":"Zhang","sequence":"first","affiliation":[{"name":"Department of Information Science and Engineering, Shandong Normal University, Jinan, China"}]},{"given":"Jun-qing","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Information Science and Engineering, Shandong Normal University, Jinan, China"},{"name":"Department of Mathematics, Yunnan Normal University, Kunming, China"}]},{"given":"Xiao-feng","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Information Engineering, HengXing University, Qingdao, China"}]},{"given":"Jie","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Big Data, Shandong Women\u2019s University, Jinan, China"}]},{"given":"Pei-yong","family":"Duan","sequence":"additional","affiliation":[{"name":"Department of Compute and Control, Yantai University, Yantai, China"}]},{"given":"Yan-yan","family":"Tan","sequence":"additional","affiliation":[{"name":"Department of Information Science and Engineering, Shandong Normal University, Jinan, China"}]}],"member":"179","published-online":{"date-parts":[[2024,3,30]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_3_3_2_1","DOI":"10.1016\/j.eswa.2022.119151"},{"key":"e_1_3_3_3_1","article-title":"A q-learning artificial bee colony for distributed assembly flow shop scheduling with factory eligibility, transportation capacity and setup time","author":"Wang J.","year":"2023","unstructured":"WangJ.TangH.LeiD., A q-learning artificial bee colony for distributed assembly flow shop scheduling with factory eligibility, transportation capacity and setup time, Engineering Applications of Artificial Intelligence: The International Journal of Intelligent Real-Time Automation (2023).","journal-title":"Engineering Applications of Artificial Intelligence: The International Journal of Intelligent Real-Time Automation"},{"doi-asserted-by":"publisher","key":"e_1_3_3_4_1","DOI":"10.1016\/j.eswa.2023.121570"},{"doi-asserted-by":"publisher","key":"e_1_3_3_5_1","DOI":"10.1016\/j.eswa.2023.122434"},{"doi-asserted-by":"publisher","key":"e_1_3_3_6_1","DOI":"10.1016\/j.ijpe.2023.109102"},{"doi-asserted-by":"publisher","key":"e_1_3_3_7_1","DOI":"10.1016\/j.knosys.2023.110309"},{"doi-asserted-by":"publisher","key":"e_1_3_3_8_1","DOI":"10.1016\/j.knosys.2022.109890"},{"doi-asserted-by":"publisher","key":"e_1_3_3_9_1","DOI":"10.1109\/TSMC.2019.2916088"},{"key":"e_1_3_3_10_1","first-page":"1","article-title":"Bi-population balancing multi-objective algorithm for fuzzy flexible job shop with energy and transportation","author":"Li J.","year":"2023","unstructured":"LiJ.HanY.GaoK.XiaoX.DuanP., Bi-population balancing multi-objective algorithm for fuzzy flexible job shop with energy and transportation, IEEE Transactions on Automation Science and Engineering (2023), 1\u201317.","journal-title":"IEEE Transactions on Automation Science and Engineering"},{"doi-asserted-by":"publisher","key":"e_1_3_3_11_1","DOI":"10.1109\/TASE.2021.3062979"},{"doi-asserted-by":"publisher","key":"e_1_3_3_12_1","DOI":"10.1109\/TETCI.2023.3271331"},{"doi-asserted-by":"publisher","key":"e_1_3_3_13_1","DOI":"10.1016\/j.asoc.2023.110598"},{"doi-asserted-by":"publisher","key":"e_1_3_3_14_1","DOI":"10.1016\/j.cie.2023.109217"},{"doi-asserted-by":"publisher","key":"e_1_3_3_15_1","DOI":"10.1016\/j.cie.2021.107378"},{"key":"e_1_3_3_16_1","article-title":"Hybrid metaheuristics for the integrated and detailed scheduling of production and delivery operations in no-wait flow shop systems","volume":"170","author":"Pereira M. Tonizza","year":"2022","unstructured":"PereiraM. Tonizza, and NaganoM. Seido, Hybrid metaheuristics for the integrated and detailed scheduling of production and delivery operations in no-wait flow shop systems, Computers & Industrial Engineering170 (2022).","journal-title":"Computers & Industrial Engineering"},{"doi-asserted-by":"publisher","key":"e_1_3_3_17_1","DOI":"10.1016\/j.swevo.2020.100804"},{"key":"e_1_3_3_18_1","article-title":"A reinforcement learning approach for flexible job shop scheduling problem with crane transportation and setup times","author":"Du Y.","year":"2022","unstructured":"DuY.LiJ.LiC.DuanP., A reinforcement learning approach for flexible job shop scheduling problem with crane transportation and setup times, IEEE Trans Neural Netw Learn Syst (2022).","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"doi-asserted-by":"publisher","key":"e_1_3_3_19_1","DOI":"10.1016\/j.asoc.2023.110022"},{"doi-asserted-by":"publisher","key":"e_1_3_3_20_1","DOI":"10.1016\/j.cie.2022.108921"},{"doi-asserted-by":"publisher","key":"e_1_3_3_21_1","DOI":"10.1016\/j.autcon.2023.104944"},{"key":"e_1_3_3_22_1","article-title":"No-idle, no-wait: When shop scheduling meets dominoes, eulerian paths and hamiltonian paths","author":"Billaut J.C.","year":"2019","unstructured":"BillautJ.C.CroceF.D.SalassaF.T\u2019KindtV., No-idle, no-wait: When shop scheduling meets dominoes, eulerian paths and hamiltonian paths, Springer US (2019).","journal-title":"Springer US"},{"key":"e_1_3_3_23_1","first-page":"654","article-title":"Fundamentals of scatter search and path relinking","volume":"29","author":"Glover M.L. Fred","year":"2000","unstructured":"GloverM.L. FredMartiRafael, Fundamentals of scatter search and path relinking, Control and Cybernetics29 (2000), 654\u2013684.","journal-title":"Control and Cybernetics"},{"key":"e_1_3_3_24_1","article-title":"A wale optimization algorithm for distributed flow shop with batch delivery","author":"Li Q.","year":"2021","unstructured":"LiQ.LiJ.ZhangX.ZhangB., A wale optimization algorithm for distributed flow shop with batch delivery, Soft Computing (2021).","journal-title":"Soft Computing"},{"doi-asserted-by":"publisher","key":"e_1_3_3_25_1","DOI":"10.1080\/0305215X.2013.827673"},{"doi-asserted-by":"publisher","key":"e_1_3_3_26_1","DOI":"10.1016\/j.jmsy.2021.10.005"},{"doi-asserted-by":"publisher","key":"e_1_3_3_27_1","DOI":"10.3233\/JIFS-219202"},{"doi-asserted-by":"publisher","key":"e_1_3_3_28_1","DOI":"10.1016\/j.eswa.2021.115453"}],"container-title":["Journal of Intelligent &amp; Fuzzy Systems: Applications in Engineering and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-238627","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.3233\/JIFS-238627","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.3233\/JIFS-238627","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T13:13:48Z","timestamp":1756905228000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.3233\/JIFS-238627"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,30]]},"references-count":27,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,8]]}},"alternative-id":["10.3233\/JIFS-238627"],"URL":"https:\/\/doi.org\/10.3233\/jifs-238627","relation":{},"ISSN":["1064-1246","1875-8967"],"issn-type":[{"type":"print","value":"1064-1246"},{"type":"electronic","value":"1875-8967"}],"subject":[],"published":{"date-parts":[[2024,3,30]]}}}