{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T07:45:14Z","timestamp":1776498314512,"version":"3.51.2"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2025,7,31]],"date-time":"2025-07-31T00:00:00Z","timestamp":1753920000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,7,31]],"date-time":"2025-07-31T00:00:00Z","timestamp":1753920000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s10586-024-05023-z","type":"journal-article","created":{"date-parts":[[2025,7,31]],"date-time":"2025-07-31T12:45:17Z","timestamp":1753965917000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Two-stage hierarchical evolutionary algorithm based on multi-population for multi-objective distributed heterogeneous welding flow shop scheduling"],"prefix":"10.1007","volume":"28","author":[{"given":"Liangcai","family":"Xia","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shijun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,31]]},"reference":[{"key":"5023_CR1","doi-asserted-by":"publisher","unstructured":"Bouaziz, N., Bettayeb, B., Sahnoun, M., et\u00a0al.: Incorporating uncertain human behavior in production scheduling for enhanced productivity in industry 5.0 context. International Journal of Production Economics 274, 109311 (2024). https:\/\/doi.org\/10.1016\/j.ijpe.2024.109311","DOI":"10.1016\/j.ijpe.2024.109311"},{"issue":"2","key":"5023_CR2","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"Deb, K., Pratap, A., Agarwal, S., et al.: A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans. Evol. Comp. 6(2), 182\u2013197 (2002). https:\/\/doi.org\/10.1109\/4235.996017","journal-title":"IEEE Trans. Evol. Comp."},{"key":"5023_CR3","doi-asserted-by":"publisher","unstructured":"Escamilla-Serna, N.J., Seck-Tuoh-Mora, J.C., Medina-Marin, J., et al.: A hybrid search using genetic algorithms and random-restart hill-climbing for flexible job shop scheduling instances with high flexibility. Applied Sciences 12(16), (2022). https:\/\/doi.org\/10.3390\/app12168050, https:\/\/www.mdpi.com\/2076-3417\/12\/16\/8050","DOI":"10.3390\/app12168050"},{"issue":"1","key":"5023_CR4","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1109\/TEVC.2022.3230822","volume":"28","author":"M Fei","year":"2024","unstructured":"Fei, M., Gong, W., Wang, L., et al.: Constrained multiobjective optimization via multitasking and knowledge transfer. IEEE Trans. Evol. Comp. 28(1), 77\u201389 (2024). https:\/\/doi.org\/10.1109\/TEVC.2022.3230822","journal-title":"IEEE Trans. Evol. Comp."},{"key":"5023_CR5","unstructured":"Golden, L.: The effects of working time on productivity and firm performance: a research synthesis paper. Conditions of Work & Employment Working Papers pp preceding 1\u201334 (2012)"},{"key":"5023_CR6","doi-asserted-by":"publisher","first-page":"100742","DOI":"10.1016\/j.swevo.2020.100742","volume":"59","author":"JP Huang","year":"2020","unstructured":"Huang, J.P., Pan, Q.K., Gao, L.: An effective iterated greedy method for the distributed permutation flowshop scheduling problem with sequence-dependent setup times. Swarm Evol. Comp. 59, 100742 (2020)","journal-title":"Swarm Evol. Comp."},{"key":"5023_CR7","doi-asserted-by":"publisher","first-page":"2077","DOI":"10.32604\/iasc.2023.040215","volume":"37","author":"K Huang","year":"2023","unstructured":"Huang, K., Li, R., Gong, W., et al.: Competitive and cooperative-based strength pareto evolutionary algorithm for green distributed heterogeneous flow shop scheduling. Intell. Auto. Soft Comp. 37, 2077\u20132101 (2023). https:\/\/doi.org\/10.32604\/iasc.2023.040215","journal-title":"Intell. Auto. Soft Comp."},{"key":"5023_CR8","doi-asserted-by":"publisher","unstructured":"Huang, K., Li, R., Gong, W., et\u00a0al.: Brce: bi-roles co-evolution for energy-efficient distributed heterogeneous permutation flow shop scheduling with flexible machine speed. Complex & Intelligent Systems 4805\u20134816 (2023). https:\/\/doi.org\/10.1007\/s40747-023-00984-x","DOI":"10.1007\/s40747-023-00984-x"},{"key":"5023_CR9","doi-asserted-by":"publisher","first-page":"178","DOI":"10.1016\/j.ins.2022.11.139","volume":"622","author":"AM Ikotun","year":"2023","unstructured":"Ikotun, A.M., Ezugwu, A.E., Abualigah, L., et al.: K-means clustering algorithms: a comprehensive review, variants analysis, and advances in the era of big data. Inf. Sci. 622, 178\u2013210 (2023)","journal-title":"Inf. Sci."},{"key":"5023_CR10","doi-asserted-by":"publisher","unstructured":"Johnson, A., Earle, T.: The evolution of human societies: From foraging group to agrarian state, second edition. Bibliovault OAI Repository, the University of Chicago Press 64 (2001). https:\/\/doi.org\/10.2307\/144131","DOI":"10.2307\/144131"},{"key":"5023_CR11","doi-asserted-by":"publisher","first-page":"117380","DOI":"10.1016\/j.eswa.2022.117380","volume":"203","author":"R Li","year":"2022","unstructured":"Li, R., Gong, W., Lu, C.: A reinforcement learning based rmoea\/d for bi-objective fuzzy flexible job shop scheduling. Exp. Syst. Appl. 203, 117380 (2022)","journal-title":"Exp. Syst. Appl."},{"key":"5023_CR12","doi-asserted-by":"publisher","first-page":"108099","DOI":"10.1016\/j.cie.2022.108099","volume":"168","author":"R Li","year":"2022","unstructured":"Li, R., Gong, W., Lu, C.: Self-adaptive multi-objective evolutionary algorithm for flexible job shop scheduling with fuzzy processing time. Comp. Ind. Eng. 168, 108099 (2022)","journal-title":"Comp. Ind. Eng."},{"issue":"4","key":"5023_CR13","doi-asserted-by":"publisher","first-page":"6550","DOI":"10.1109\/TASE.2023.3327792","volume":"21","author":"R Li","year":"2024","unstructured":"Li, R., Gong, W., Wang, L., et al.: Double dqn-based coevolution for green distributed heterogeneous hybrid flowshop scheduling with multiple priorities of jobs. IEEE Trans. Auto. Sci. Eng. 21(4), 6550\u20136562 (2024). https:\/\/doi.org\/10.1109\/TASE.2023.3327792","journal-title":"IEEE Trans. Auto. Sci. Eng."},{"key":"5023_CR14","doi-asserted-by":"publisher","first-page":"108775","DOI":"10.1016\/j.engappai.2024.108775","volume":"135","author":"R Li","year":"2024","unstructured":"Li, R., Wang, L., Gong, W., et al.: Evolutionary computation and reinforcement learning integrated algorithm for distributed heterogeneous flowshop scheduling. Eng. Appl. Artif. Intell. 135, 108775 (2024)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"5023_CR15","doi-asserted-by":"publisher","unstructured":"Li, R., Wang, L., Gong, W., et\u00a0al.: An evolutionary multitasking memetic algorithm for multi-objective distributed heterogeneous welding flow shop scheduling. IEEE Transactions on Evolutionary Computation 1\u20131 (2024). https:\/\/doi.org\/10.1109\/TEVC.2024.3393620","DOI":"10.1109\/TEVC.2024.3393620"},{"key":"5023_CR16","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1016\/j.ijpe.2016.01.016","volume":"174","author":"X Li","year":"2016","unstructured":"Li, X., Gao, L.: An effective hybrid genetic algorithm and tabu search for flexible job shop scheduling problem. Int. J. Prod. Eco. 174, 93\u2013110 (2016)","journal-title":"Int. J. Prod. Eco."},{"key":"5023_CR17","doi-asserted-by":"publisher","unstructured":"Li, X., Xiao, S., Wang, C., et al.: Mathematical modeling and a discrete artificial bee colony algorithm for the welding shop scheduling problem. Memetic Computing 1\u201319 (2019). https:\/\/doi.org\/10.1007\/s12293-019-00283-4","DOI":"10.1007\/s12293-019-00283-4"},{"key":"5023_CR18","doi-asserted-by":"publisher","first-page":"161","DOI":"10.1016\/j.advengsoft.2016.06.004","volume":"99","author":"C Lu","year":"2016","unstructured":"Lu, C., Xiao, S., Li, X., et al.: An effective multi-objective discrete grey wolf optimizer for a real-world scheduling problem in welding production. Adv. Eng. Softw. 99, 161\u2013176 (2016)","journal-title":"Adv. Eng. Softw."},{"key":"5023_CR19","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.engappai.2016.10.013","volume":"57","author":"C Lu","year":"2017","unstructured":"Lu, C., Gao, L., Li, X., et al.: A hybrid multi-objective grey wolf optimizer for dynamic scheduling in a real-world welding industry. Eng. Appl. Artif. Intell. 57, 61\u201379 (2017)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"5023_CR20","unstructured":"Lu, C., Tian, H., LI X, et al.: Energy-efficient distributed welding scheduling based on a multi-objective seagull optimization algorithm. Journal of Mechanical Engineering 1\u201312 (2023)"},{"issue":"1","key":"5023_CR21","doi-asserted-by":"publisher","first-page":"963","DOI":"10.1109\/TII.2023.3271749","volume":"20","author":"C Lu","year":"2024","unstructured":"Lu, C., Gao, R., Yin, L., et al.: Human-robot collaborative scheduling in energy-efficient welding shop. IEEE Trans. Ind. Inf. 20(1), 963\u2013971 (2024). https:\/\/doi.org\/10.1109\/TII.2023.3271749","journal-title":"IEEE Trans. Ind. Inf."},{"key":"5023_CR22","doi-asserted-by":"publisher","first-page":"106454","DOI":"10.1016\/j.engappai.2023.106454","volume":"123","author":"C Luo","year":"2023","unstructured":"Luo, C., Gong, W., Li, R., et al.: Problem-specific knowledge moea\/d for energy-efficient scheduling of distributed permutation flow shop in heterogeneous factories. Eng. Appl. Artif. Intell. 123, 106454 (2023)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"1","key":"5023_CR23","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ejor.2023.02.001","volume":"312","author":"P Perez-Gonzalez","year":"2024","unstructured":"Perez-Gonzalez, P., Framinan, J.M.: A review and classification on distributed permutation flowshop scheduling problems. Eur. J. Operat. Res. 312(1), 1\u201321 (2024)","journal-title":"Eur. J. Operat. Res."},{"issue":"2","key":"5023_CR24","doi-asserted-by":"publisher","first-page":"263","DOI":"10.1109\/TEVC.2022.3145582","volume":"26","author":"K Qiao","year":"2022","unstructured":"Qiao, K., Yu, K., Qu, B., et al.: An evolutionary multitasking optimization framework for constrained multiobjective optimization problems. IEEE Trans. Evol. Comp. 26(2), 263\u2013277 (2022). https:\/\/doi.org\/10.1109\/TEVC.2022.3145582","journal-title":"IEEE Trans. Evol. Comp."},{"issue":"10","key":"5023_CR25","doi-asserted-by":"publisher","first-page":"1951","DOI":"10.1109\/JAS.2023.123336","volume":"10","author":"K Qiao","year":"2023","unstructured":"Qiao, K., Liang, J., Liu, Z., et al.: Evolutionary multitasking with global and local auxiliary tasks for constrained multi-objective optimization. IEEE\/CAA J. Auto. Sinica 10(10), 1951\u20131964 (2023). https:\/\/doi.org\/10.1109\/JAS.2023.123336","journal-title":"IEEE\/CAA J. Auto. Sinica"},{"key":"5023_CR26","unstructured":"Roy, R., St, C.: Design of Experiments Using The Taguchi Approach 16 Steps to Product and Process Improvement (2022)"},{"issue":"2","key":"5023_CR27","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1162\/106365600568158","volume":"8","author":"DAV Veldhuizen","year":"2000","unstructured":"Veldhuizen, D.A.V., Lamont, G.B.: Multiobjective evolutionary algorithms: analyzing the state-of-the-art. Evol. Comp. 8(2), 125\u2013147 (2000). https:\/\/doi.org\/10.1162\/106365600568158","journal-title":"Evol. Comp."},{"key":"5023_CR28","doi-asserted-by":"publisher","first-page":"373","DOI":"10.1016\/j.jmsy.2020.06.020","volume":"56","author":"B Wang","year":"2020","unstructured":"Wang, B., Hu, S.J., Sun, L., et al.: Intelligent welding system technologies: State-of-the-art review and perspectives. J. Manuf. Syst. 56, 373\u2013391 (2020)","journal-title":"J. Manuf. Syst."},{"key":"5023_CR29","doi-asserted-by":"publisher","first-page":"100858","DOI":"10.1016\/j.swevo.2021.100858","volume":"62","author":"G Wang","year":"2021","unstructured":"Wang, G., Li, X., Gao, L., et al.: Energy-efficient distributed heterogeneous welding flow shop scheduling problem using a modified moea\/d. Swarm Evol. Comp. 62, 100858 (2021)","journal-title":"Swarm Evol. Comp."},{"key":"5023_CR30","doi-asserted-by":"publisher","unstructured":"Wang, G., Li, X., Gao, L., et\u00a0al.: An effective multi-objective whale swarm algorithm for energy-efficient scheduling of distributed welding flow shop. Annals of Operations Research 223\u2013255 (2022). https:\/\/doi.org\/10.1007\/s10479-021-03952-1","DOI":"10.1007\/s10479-021-03952-1"},{"key":"5023_CR31","doi-asserted-by":"publisher","first-page":"105877","DOI":"10.1016\/j.engappai.2023.105877","volume":"120","author":"J Wang","year":"2023","unstructured":"Wang, J., Wang, L., Xiu, X.: A cooperative memetic algorithm for energy-aware distributed welding shop scheduling problem. Eng. Appl. Artif. Intell. 120, 105877 (2023)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"5023_CR32","doi-asserted-by":"publisher","unstructured":"Wang, Y., Wu, L., Yuan, X.: Multi-objective self-adaptive differential evolution with elitist archive and crowding entropy-based diversity measure. Soft Computing 193\u2013209 (2010). https:\/\/doi.org\/10.1007\/s00500-008-0394-9","DOI":"10.1007\/s00500-008-0394-9"},{"issue":"1","key":"5023_CR33","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1109\/TEVC.2005.851275","volume":"10","author":"L While","year":"2006","unstructured":"While, L., Hingston, P., Barone, L., et al.: A faster algorithm for calculating hypervolume. IEEE Trans. Evol. Comp. 10(1), 29\u201338 (2006). https:\/\/doi.org\/10.1109\/TEVC.2005.851275","journal-title":"IEEE Trans. Evol. Comp."},{"issue":"1","key":"5023_CR34","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/j.ssresearch.2010.04.005","volume":"40","author":"S Yang","year":"2011","unstructured":"Yang, S., Zheng, L.: The paradox of de-coupling: a study of flexible work program and workers\u2019 productivity. Soc. Sci. Res. 40(1), 299\u2013311 (2011)","journal-title":"Soc. Sci. Res."},{"key":"5023_CR35","doi-asserted-by":"publisher","first-page":"101574","DOI":"10.1016\/j.swevo.2024.101574","volume":"87","author":"L Yao","year":"2024","unstructured":"Yao, L., Chen, J., Wang, L., et al.: Multi-objective optimization driven by preponderant individuals and symmetric sampling for operational parameter design in aluminum electrolysis process. Swarm Evol. Comp. 87, 101574 (2024)","journal-title":"Swarm Evol. Comp."},{"issue":"1","key":"5023_CR36","doi-asserted-by":"publisher","first-page":"2107301","DOI":"10.1080\/2331186X.2022.2107301","volume":"9","author":"MH Yimam","year":"2022","unstructured":"Yimam, M.H.: Impact of training on employees performance: a case study of bahir dar university, ethiopia. Cogent Edu. 9(1), 2107301 (2022). https:\/\/doi.org\/10.1080\/2331186X.2022.2107301","journal-title":"Cogent Edu."},{"key":"5023_CR37","doi-asserted-by":"publisher","unstructured":"Zhang, F., Li, C., Li, R., et\u00a0al.: Intelligent learning-based cooperative and competitive multi-objective optimization for energy-aware distributed heterogeneous welding shop scheduling. Complex & Intelligent Systems 3459\u20133471 (2024). https:\/\/doi.org\/10.1007\/s40747-023-01335-6","DOI":"10.1007\/s40747-023-01335-6"},{"issue":"4","key":"5023_CR38","doi-asserted-by":"publisher","first-page":"3563","DOI":"10.1016\/j.eswa.2010.08.145","volume":"38","author":"G Zhang","year":"2011","unstructured":"Zhang, G., Gao, L., Shi, Y.: An effective genetic algorithm for the flexible job-shop scheduling problem. Exp. Syst. Appl. 38(4), 3563\u20133573 (2011)","journal-title":"Exp. Syst. Appl."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-024-05023-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-024-05023-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-024-05023-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,9]],"date-time":"2025-09-09T17:41:57Z","timestamp":1757439717000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-024-05023-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,31]]},"references-count":38,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["5023"],"URL":"https:\/\/doi.org\/10.1007\/s10586-024-05023-z","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,7,31]]},"assertion":[{"value":"3 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 December 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 December 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 July 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no Conflict of interest","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"442"}}