{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T21:48:54Z","timestamp":1778708934057,"version":"3.51.4"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T00:00:00Z","timestamp":1733097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Wuhan East Lake District Unveiling the List of Hanging Project","award":["2022KJB101"],"award-info":[{"award-number":["2022KJB101"]}]},{"name":"Hubei Key Laboratory of Electronic Manufacturing and Packaging Integration","award":["EMPI2023024"],"award-info":[{"award-number":["EMPI2023024"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s10489-024-05928-7","type":"journal-article","created":{"date-parts":[[2024,12,2]],"date-time":"2024-12-02T12:16:49Z","timestamp":1733141809000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Multi-objective optimization of the mixed-flow intelligent production line for automotive MEMS pressure sensors"],"prefix":"10.1007","volume":"55","author":[{"given":"Quanyong","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4404-8845","authenticated-orcid":false,"given":"Hui","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shengnan","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wan","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanshun","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,2]]},"reference":[{"key":"5928_CR1","doi-asserted-by":"publisher","first-page":"118879","DOI":"10.1016\/j.eswa.2022.118879","volume":"213","author":"B Zeng","year":"2023","unstructured":"Zeng B, Li H, Mao C, Wu Y (2023) Modeling, prediction and analysis of new energy vehicle sales in China using a variable-structure grey model. Expert Syst Appl 213:118879","journal-title":"Expert Syst Appl"},{"key":"5928_CR2","doi-asserted-by":"publisher","first-page":"101021","DOI":"10.1016\/j.swevo.2021.101021","volume":"68","author":"QH Tang","year":"2022","unstructured":"Tang QH, Meng K, Cheng LX, Zhang ZK (2022) An improved multi-objective multifactorial evolutionary algorithm for assembly line balancing problem considering regular production and preventive maintenance scenarios. Swarm Evol Comput 68:101021","journal-title":"Swarm Evol Comput"},{"issue":"10","key":"5928_CR3","doi-asserted-by":"publisher","first-page":"168781401773324","DOI":"10.1177\/1687814017733246","volume":"9","author":"MK Zheng","year":"2017","unstructured":"Zheng MK, Ming XG (2017) Construction of cyber-physical system\u2013integrated smart manufacturing workshops: a case study in automobile industry. Adv Mech Eng 9(10):1687814017733246","journal-title":"Adv Mech Eng"},{"issue":"5","key":"5928_CR4","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1108\/AA-12-2020-0196","volume":"41","author":"H Zhang","year":"2021","unstructured":"Zhang H, Li XY, Kan Z, Zhang XH, Li ZY (2021) Research on optimization of assembly line based on product scheduling and just-in-time feeding of parts. Assembly Autom 41(5):577\u2013588","journal-title":"Assembly Autom"},{"key":"5928_CR5","doi-asserted-by":"publisher","first-page":"1665","DOI":"10.1007\/s00170-014-5944-y","volume":"73","author":"P Sivasankaran","year":"2014","unstructured":"Sivasankaran P, Shahabudeen P (2014) Literature review of assembly line balancing problems. Int J Adv Manufact Technol 73:1665\u20131694","journal-title":"Int J Adv Manufact Technol"},{"issue":"2","key":"5928_CR6","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1016\/j.ejor.2006.10.010","volume":"183","author":"N Boysen","year":"2007","unstructured":"Boysen N, Fliedner M, Scholl A (2007) A classification of assembly line balancing problems. Eur J Oper Res 183(2):674\u2013693","journal-title":"Eur J Oper Res"},{"key":"5928_CR7","doi-asserted-by":"crossref","unstructured":"Antunes CH, Rasouli V, Alves MJ, Gomes A, Costa JJ, Gaspar A (2020) A discussion of mixed integer linear programming models of thermostatic loads in demand response. In:\u00a0Advances in energy system optimization: proceedings of the 2nd international symposium on energy system optimization 2. Springer International Publishing,\u00a0pp 105\u2013122","DOI":"10.1007\/978-3-030-32157-4_7"},{"key":"5928_CR8","doi-asserted-by":"publisher","first-page":"102251","DOI":"10.1016\/j.rcim.2021.102251","volume":"73","author":"T Yin","year":"2022","unstructured":"Yin T, Zhang ZQ, Zhang Y, Wu TF, Liang W (2022) Mixed-integer programming model and hybrid driving algorithm for multi-product partial disassembly line balancing problem with multi-robot workstations. Robot Cim-Int Manuf 73:102251","journal-title":"Robot Cim-Int Manuf"},{"key":"5928_CR9","doi-asserted-by":"publisher","first-page":"106394","DOI":"10.1016\/j.asoc.2020.106394","volume":"93","author":"ZA Cil","year":"2020","unstructured":"Cil ZA, Li ZX, Mete S, Ozceylan E (2020) Mathematical model and bee algorithms for mixed-model assembly line balancing problem with physical human\u2013robot collaboration. Appl Soft Comput 93:106394","journal-title":"Appl Soft Comput"},{"key":"5928_CR10","doi-asserted-by":"publisher","first-page":"2913","DOI":"10.1007\/s10845-015-1150-5","volume":"30","author":"I Kucukkoc","year":"2019","unstructured":"Kucukkoc I, Buyukozkan K, Satoglu SI, Zhang DZ (2019) A mathematical model and artificial bee colony algorithm for the lexicographic bottleneck mixed-model assembly line balancing problem. J Intel Manuf 30:2913\u20132925","journal-title":"J Intel Manuf"},{"key":"5928_CR11","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1016\/j.apm.2019.02.019","volume":"72","author":"P Samouei","year":"2019","unstructured":"Samouei P, Ashayeri J (2019) Developing optimization & robust models for a mixed-model assembly line balancing problem with semi-automated operations. Appl math model 72:259\u2013275","journal-title":"Appl math model"},{"issue":"1","key":"5928_CR12","doi-asserted-by":"publisher","first-page":"395","DOI":"10.1007\/s13198-021-01284-8","volume":"13","author":"A Yadav","year":"2022","unstructured":"Yadav A, Agrawal S (2022) Mathematical model for robotic two-sided assembly line balancing problem with zoning constraints. Int J Syst Assur Eng 13(1):395\u2013408","journal-title":"Int J Syst Assur Eng"},{"issue":"2","key":"5928_CR13","first-page":"114","volume":"6","author":"B Orazbayev","year":"2021","unstructured":"Orazbayev B, Moldasheva Z, Orazbayeva K, Makhatova V, Kurmangaziyeva L, Gabdulova A (2021) Development of mathematical models and optimization of operation modes of the oil heating station of main oil pipelines under conditions of fuzzy initial information. East-Eur J Enterp Technol 6(2):114","journal-title":"East-Eur J Enterp Technol"},{"key":"5928_CR14","doi-asserted-by":"publisher","first-page":"8217","DOI":"10.1007\/s00521-019-04293-8","volume":"32","author":"M Salehi","year":"2020","unstructured":"Salehi M, Maleki HR, Niroomand S (2020) Solving a new cost-oriented assembly line balancing problem by classical and hybrid meta-heuristic algorithms. Neural Comput Appl 32:8217\u20138243","journal-title":"Neural Comput Appl"},{"issue":"6","key":"5928_CR15","doi-asserted-by":"publisher","first-page":"4723","DOI":"10.1007\/s00521-022-07989-6","volume":"35","author":"Q Wang","year":"2023","unstructured":"Wang Q, He YQ, Tang CL (2023) Mastering construction heuristics with self-play deep reinforcement learning. Neural Comput Appl 35(6):4723\u20134738","journal-title":"Neural Comput Appl"},{"issue":"1","key":"5928_CR16","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1007\/s10489-019-01522-4","volume":"50","author":"G Dhiman","year":"2020","unstructured":"Dhiman G (2020) MOSHEPO: a hybrid multi-objective approach to solve economic load dispatch and micro grid problems. Appl Intell 50(1):119\u2013137","journal-title":"Appl Intell"},{"key":"5928_CR17","doi-asserted-by":"publisher","first-page":"101191","DOI":"10.1016\/j.swevo.2022.101191","volume":"75","author":"L Wen","year":"2022","unstructured":"Wen L, Gao L, Li XY, Li H (2022) A new genetic algorithm based evolutionary neural architecture search for image classification. Swarm Evol Comput 75:101191","journal-title":"Swarm Evol Comput"},{"key":"5928_CR18","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.swevo.2019.06.009","volume":"49","author":"F Wang","year":"2019","unstructured":"Wang F, Li YX, Zhang H, Hu T, Shen XL (2019) An adaptive weight vector guided evolutionary algorithm for preference-based multi-objective optimization. Swarm Evol Comput 49:220\u2013233","journal-title":"Swarm Evol Comput"},{"key":"5928_CR19","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1007\/s10489-016-0825-8","volume":"46","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili S, Jangir P, Saremi S (2017) Multi-objective ant lion optimizer: a multi-objective optimization algorithm for solving engineering problems. Appl Intell 46:79\u201395","journal-title":"Appl Intell"},{"key":"5928_CR20","doi-asserted-by":"publisher","first-page":"104905","DOI":"10.1016\/j.cor.2020.104905","volume":"118","author":"ZK Zhang","year":"2020","unstructured":"Zhang ZK, Tang QH, Ruiz R, Zhang LP (2020) Ergonomic risk and cycle time minimization for the U-shaped worker assignment assembly line balancing problem: a multi-objective approach. Comput Oper Res 118:104905","journal-title":"Comput Oper Res"},{"key":"5928_CR21","doi-asserted-by":"crossref","unstructured":"Chantarasamai K, Lasunon\u00a0O-U\u00a0(2021) Modified differential evolution algorithm for U-shaped assembly line balancing type 2. Int J Intell Eng Syst 14(4): 452\u2013462","DOI":"10.22266\/ijies2021.0831.39"},{"key":"5928_CR22","doi-asserted-by":"publisher","first-page":"104593","DOI":"10.1016\/j.engappai.2021.104593","volume":"109","author":"LP Zhao","year":"2022","unstructured":"Zhao LP, Tang QH, Zhang ZK (2022) An improved preference-based variable neighborhood search algorithm with ar-dominance for assembly line balancing considering preventive maintenance scenarios. Eng Appl Artif Intel 109:104593","journal-title":"Eng Appl Artif Intel"},{"key":"5928_CR23","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.engappai.2015.03.005","volume":"47","author":"XS Zhao","year":"2016","unstructured":"Zhao XS, Hsu CY, Chang PC, Li L (2016) A genetic algorithm for the multi-objective optimization of mixed-model assembly line based on the mental workload. Eng Appl Artif Intel 47:140\u2013146","journal-title":"Eng Appl Artif Intel"},{"issue":"2","key":"5928_CR24","doi-asserted-by":"publisher","first-page":"580","DOI":"10.1080\/00207543.2021.2011464","volume":"61","author":"JH Chen","year":"2023","unstructured":"Chen JH, Jia XL, He QX (2023) A novel bi-level multi-objective genetic algorithm for integrated assembly line balancing and part feeding problem. Int J Prod Res 61(2):580\u2013603","journal-title":"Int J Prod Res"},{"key":"5928_CR25","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1016\/j.cie.2017.08.029","volume":"112","author":"M Bortolini","year":"2017","unstructured":"Bortolini M, Faccio M, Gamberi M, Pilati F (2017) Multi-objective assembly line balancing considering component picking and ergonomic risk. Comput Ind Eng 112:348\u2013367","journal-title":"Comput Ind Eng"},{"key":"5928_CR26","doi-asserted-by":"publisher","first-page":"120600","DOI":"10.1016\/j.eswa.2023.120600","volume":"229","author":"YR Chen","year":"2023","unstructured":"Chen YR, Zhong JY, Mumtaz J, Zhou SW, Zhu LX (2023) An improved spider monkey optimization algorithm for multi-objective planning and scheduling problems of PCB assembly line. Expert Syst Appl 229:120600","journal-title":"Expert Syst Appl"},{"key":"5928_CR27","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.cirpj.2023.09.002","volume":"47","author":"A Nourmohammadi","year":"2023","unstructured":"Nourmohammadi A, Ng AH, Fathi M, Vollebregt J, Hanson L (2023) Multi-objective optimization of mixed-model assembly lines incorporating musculoskeletal risks assessment using digital human modeling. CIRP J Manuf Sci Tec 47:71\u201385","journal-title":"CIRP J Manuf Sci Tec"},{"key":"5928_CR28","doi-asserted-by":"publisher","first-page":"102121","DOI":"10.1016\/j.aei.2023.102121","volume":"57","author":"C Zhang","year":"2023","unstructured":"Zhang C, Wang ZH, Zhou GH, Chang FT, Ma DX, Jing YZ, Cheng W, Ding K, Zhao D (2023) Towards new-generation human-centric smart manufacturing in industry 5.0: a systematic review. Adv Eng Inform 57:102121","journal-title":"Adv Eng Inform"},{"key":"5928_CR29","doi-asserted-by":"publisher","first-page":"101779","DOI":"10.1016\/j.aei.2022.101779","volume":"54","author":"QY Zhang","year":"2022","unstructured":"Zhang QY, Shen SN, Li H, Cao W, Tang W, Jiang J, Deng MX, Zhang YF, Gu BK, Wu KK, Zhang K, Liu S (2022) Digital twin-driven intelligent production line for automotive MEMS pressure sensors. Adv Eng Inform 54:101779","journal-title":"Adv Eng Inform"},{"issue":"1","key":"5928_CR30","doi-asserted-by":"publisher","first-page":"56","DOI":"10.3390\/mi11010056","volume":"11","author":"PS Song","year":"2020","unstructured":"Song PS, Ma Z, Ma J, Yang LL, Wei JT, Zhao YM, Zhang ML, Yang FH, Wang XD (2020) Recent progress of miniature MEMS pressure sensors. Micromachines 11(1):56","journal-title":"Micromachines"},{"issue":"12","key":"5928_CR31","doi-asserted-by":"publisher","first-page":"04020143","DOI":"10.1061\/(ASCE)CO.1943-7862.0001940","volume":"146","author":"S Abbasi","year":"2020","unstructured":"Abbasi S, Taghizade K, Noorzai E (2020) BIM-based combination of takt time and discrete event simulation for implementing just in time in construction scheduling under constraints. J Constr Eng M 146(12):04020143","journal-title":"J Constr Eng M"},{"issue":"3","key":"5928_CR32","doi-asserted-by":"publisher","first-page":"240","DOI":"10.1504\/IJCAT.2020.106571","volume":"62","author":"JX Chen","year":"2020","unstructured":"Chen JX, Zhao F, Sun YG, Yin YL (2020) Improved XGBoost model based on genetic algorithm. Int J Comput Appl T 62(3):240\u2013245","journal-title":"Int J Comput Appl T"},{"issue":"5","key":"5928_CR33","doi-asserted-by":"publisher","first-page":"7","DOI":"10.12700\/APH.17.5.2020.5.1","volume":"17","author":"J Cabala","year":"2020","unstructured":"Cabala J, Jadlovsky J (2020) Choosing the optimal production strategy by multi-objective optimization methods. Acta Polytech Hung 17(5):7\u201325","journal-title":"Acta Polytech Hung"},{"key":"5928_CR34","doi-asserted-by":"publisher","first-page":"111418","DOI":"10.1016\/j.oceaneng.2022.111418","volume":"255","author":"C Ntakolia","year":"2022","unstructured":"Ntakolia C, Lyridis D (2022) A comparative study on ant colony optimization algorithm approaches for solving multi-objective path planning problems in case of unmanned surface vehicles. Ocean Eng 255:111418","journal-title":"Ocean Eng"},{"key":"5928_CR35","doi-asserted-by":"publisher","first-page":"107294","DOI":"10.1016\/j.compeleceng.2021.107294","volume":"94","author":"A Hafez","year":"2021","unstructured":"Hafez A, Abdelaziz A, Hendy M, Ali F (2021) Optimal sizing of off-line microgrid via hybrid multi-objective simulated annealing particle swarm optimizer. Comput Electr Eng 94:107294","journal-title":"Comput Electr Eng"},{"issue":"12","key":"5928_CR36","doi-asserted-by":"publisher","first-page":"15095","DOI":"10.1007\/s10489-022-04275-9","volume":"53","author":"SP Liang","year":"2023","unstructured":"Liang SP, Liu Z, You DL, Pan WW, Zhao JJ, Cao YF (2023) PSO-NRS: an online group feature selection algorithm based on PSO multi-objective optimization. Appl Intell 53(12):15095\u201315111","journal-title":"Appl Intell"},{"key":"5928_CR37","doi-asserted-by":"publisher","first-page":"1135","DOI":"10.1007\/s10586-020-03179-y","volume":"24","author":"E Mirsadeghi","year":"2021","unstructured":"Mirsadeghi E, Khodayifar S (2021) Hybridizing particle swarm optimization with simulated annealing and differential evolution. Cluster Comput 24:1135\u20131163","journal-title":"Cluster Comput"},{"key":"5928_CR38","doi-asserted-by":"publisher","first-page":"76333","DOI":"10.1109\/ACCESS.2020.2987057","volume":"8","author":"A Usman","year":"2020","unstructured":"Usman A, Yusof U, Naim S (2020) Filter-based multi-objective feature selection using NSGA III and cuckoo optimization algorithm. IEEE Access 8:76333\u201376356","journal-title":"IEEE Access"},{"issue":"9","key":"5928_CR39","doi-asserted-by":"publisher","first-page":"1274","DOI":"10.1016\/j.eng.2021.04.022","volume":"7","author":"H Zhou","year":"2021","unstructured":"Zhou H, Yang CJ, Sun YX (2021) Intelligent ironmaking optimization service on a cloud computing platform by digital twin. Eng 7(9):1274\u20131281","journal-title":"Eng"},{"key":"5928_CR40","doi-asserted-by":"publisher","first-page":"107616","DOI":"10.1016\/j.cie.2021.107616","volume":"161","author":"W Zhang","year":"2021","unstructured":"Zhang W, Hou L, Jiao RJ (2021) Dynamic takt time decisions for paced assembly lines balancing and sequencing considering highly mixed-model production: an improved artificial bee colony optimization approach. Comput Ind Eng 161:107616","journal-title":"Comput Ind Eng"},{"key":"5928_CR41","doi-asserted-by":"publisher","first-page":"102682","DOI":"10.1016\/j.rcim.2023.102682","volume":"86","author":"G Yuan","year":"2024","unstructured":"Yuan G, Liu XJ, Zhu CB, Wang CX, Zhu MH, Sun Y (2024) Multi-objective coupling optimization of electrical cable intelligent production line driven by digital twin. Robot and Cim-Int Manuf 86:102682","journal-title":"Robot and Cim-Int Manuf"},{"issue":"9","key":"5928_CR42","doi-asserted-by":"publisher","first-page":"2884","DOI":"10.1080\/00207543.2021.1905902","volume":"60","author":"J Guo","year":"2022","unstructured":"Guo J, Pu ZP, Du BG, Li YB (2022) Multi-objective optimisation of stochastic hybrid production line balancing including assembly and disassembly tasks. Int J Prod Res 60(9):2884\u20132900","journal-title":"Int J Prod Res"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05928-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-05928-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05928-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,2]],"date-time":"2025-01-02T15:16:54Z","timestamp":1735831014000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-05928-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,2]]},"references-count":42,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["5928"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-05928-7","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,2]]},"assertion":[{"value":"16 October 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 December 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not required.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Not required.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"The authors disclose no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The authors approved to publish this article.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}],"article-number":"72"}}