{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:41:16Z","timestamp":1775068876517,"version":"3.50.1"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T00:00:00Z","timestamp":1659571200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2023,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>This paper addresses a multi-objective energy-efficient scheduling problem of the distributed permutation flowshop with sequence-dependent setup time and no-wait constraints (EEDNWFSP), which have important practical applications. Two objectives minimization of both makespan and total energy consumption (TEC) are considered simultaneously. To address this problem, a new mixed-integer linear programming (MILP) model is formulated. Considering the issues faced in solving large-scale instances, an improved non-dominated sorting genetic algorithm (INSGA-II) is further proposed that uses two variants of the Nawaz-Enscore-Ham heuristic (NEH) to generate high-quality initial population. Moreover, two problem-specific speed adjustment heuristics are presented, which can enhance the qualities of the obtained non-dominated solutions. In addition, four local and two global search operators are designed to improve the exploration and exploitation abilities of the proposed algorithm. The effectiveness of the proposed algorithm was verified using extensive computational tests and comparisons. The experimental results show that the proposed INSGA-II is more effective compared to other efficient multi-objective algorithms.<\/jats:p>","DOI":"10.1007\/s40747-022-00830-6","type":"journal-article","created":{"date-parts":[[2022,8,4]],"date-time":"2022-08-04T18:02:37Z","timestamp":1659636157000},"page":"825-849","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Improved NSGA-II for energy-efficient distributed no-wait flow-shop with sequence-dependent setup time"],"prefix":"10.1007","volume":"9","author":[{"given":"Qing-qing","family":"Zeng","sequence":"first","affiliation":[]},{"given":"Jun-qing","family":"Li","sequence":"additional","affiliation":[]},{"given":"Rong-hao","family":"Li","sequence":"additional","affiliation":[]},{"given":"Ti-hao","family":"Huang","sequence":"additional","affiliation":[]},{"given":"Yu-yan","family":"Han","sequence":"additional","affiliation":[]},{"given":"Hong-yan","family":"Sang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,8,4]]},"reference":[{"key":"830_CR1","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4615-6383-9","volume-title":"Integrated product, process and enterprise design: why, what and how?","author":"B Wang","year":"1997","unstructured":"Wang B, Han K, Spoerre J et al (1997) Integrated product, process and enterprise design: why, what and how? Springer"},{"issue":"3","key":"830_CR2","volume":"62","author":"G Wang","year":"2021","unstructured":"Wang G, Li X, Gao L et al (2021) Energy-efficient distributed heterogeneous welding flow shop scheduling problem using a modified MOEA\/D. Swarm Evol Comput 62(3):100858","journal-title":"Swarm Evol Comput"},{"key":"830_CR3","volume":"94","author":"X Wu","year":"2020","unstructured":"Wu X, Che A, Lev B (2020) Energy-efficient no-wait permutation flow shop scheduling by adaptive multi-objective variable neighborhood search. Omega 94:102117","journal-title":"Omega"},{"key":"830_CR4","doi-asserted-by":"crossref","first-page":"2197","DOI":"10.1016\/j.cor.2004.02.009","volume":"32","author":"J Grabowski","year":"2005","unstructured":"Grabowski J, Pempera J (2005) Some local search algorithms for no-wait flow-shop problem with makespan criterion. Comput Oper Res 32:2197\u20132212","journal-title":"Comput Oper Res"},{"key":"830_CR5","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1016\/j.cor.2009.06.019","volume":"37","author":"R Ruiz","year":"2010","unstructured":"Ruiz R, Naderi B (2010) The distributed permutation flowshop scheduling problem. Comput Oper Res 37:754\u2013768","journal-title":"Comput Oper Res"},{"key":"830_CR6","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2020.100742","volume":"59","author":"JP Huang","year":"2020","unstructured":"Huang JP, Pan QK, Gao L (2020) An effective iterated greedy method for the distributed permutation flowshop scheduling problem with sequence-dependent setup times. Swarm Evol Comput 59:100742","journal-title":"Swarm Evol Comput"},{"issue":"5","key":"830_CR7","doi-asserted-by":"crossref","first-page":"1805","DOI":"10.1109\/TSMC.2017.2788879","volume":"50","author":"JJ Wang","year":"2018","unstructured":"Wang JJ, Wang L (2018) A knowledge-based cooperative algorithm for energy-efficient scheduling of distributed flow-shop. IEEE Trans Syst Man Cybern Syst 50(5):1805\u20131819","journal-title":"IEEE Trans Syst Man Cybern Syst"},{"key":"830_CR8","volume":"57","author":"GC Wang","year":"2020","unstructured":"Wang GC, Gao L, Li XY et al (2020) Energy-efficient distributed permutation flow shop scheduling problem using a multi-objective whale swarm algorithm. Swarm Evol Comput 57:100716","journal-title":"Swarm Evol Comput"},{"key":"830_CR9","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1016\/j.cie.2018.03.014","volume":"118","author":"V Fernandez-Viagas","year":"2018","unstructured":"Fernandez-Viagas V, Perez-Gonzalez P, Framinan JM (2018) The distributed permutation flow shop to minimise the total flowtime. Comput Ind Eng 118:464\u2013477","journal-title":"Comput Ind Eng"},{"key":"830_CR10","volume":"60","author":"C Lu","year":"2021","unstructured":"Lu C, Gao L, Gong W et al (2021) Sustainable scheduling of distributed permutation flow-shop with non-identical factory using a knowledge-based multi-objective memetic optimization algorithm. Swarm Evol Comput 60:100803","journal-title":"Swarm Evol Comput"},{"issue":"13","key":"830_CR11","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.ifacol.2019.11.142","volume":"52","author":"G Wang","year":"2019","unstructured":"Wang G, Li X, Gao L et al (2019) A multi-objective whale swarm algorithm for energy-efficient distributed permutation flow shop scheduling problem with sequence dependent setup times. IFAC-PapersOnLine 52(13):235\u2013240","journal-title":"IFAC-PapersOnLine"},{"key":"830_CR12","volume":"2020","author":"Y Li","year":"2020","unstructured":"Li Y, Li X, Gao L et al (2020) An improved artificial bee colony algorithm for distributed heterogeneous hybrid flowshop scheduling problem with sequence-dependent setup times. Comput Ind Eng 2020:106638","journal-title":"Comput Ind Eng"},{"issue":"6","key":"830_CR13","doi-asserted-by":"crossref","first-page":"2425","DOI":"10.1109\/TCYB.2019.2943606","volume":"50","author":"JQ Li","year":"2020","unstructured":"Li JQ, Song MX, Wang L et al (2020) Hybrid artificial bee colony algorithm for a parallel batching distributed flow-shop problem with deteriorating jobs. IEEE Trans Cybern 50(6):2425\u20132439","journal-title":"IEEE Trans Cybern"},{"key":"830_CR14","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.105527","volume":"194","author":"W Shao","year":"2020","unstructured":"Shao W, Shao Z, Pi D (2020) Modeling and multi-neighborhood iterated greedy algorithm for distributed hybrid flow shop scheduling problem. Knowl-Based Syst 194:105527","journal-title":"Knowl-Based Syst"},{"key":"830_CR15","volume":"90","author":"J Cai","year":"2020","unstructured":"Cai J, Zhou R, Lei D (2020) Dynamic shuffled frog-leaping algorithm for distributed hybrid flow shop scheduling with multiprocessor tasks. Eng Appl Artif Intell 90:103540","journal-title":"Eng Appl Artif Intell"},{"key":"830_CR16","volume":"60","author":"ZQ Zhang","year":"2021","unstructured":"Zhang ZQ, Qian B, Hu R et al (2021) A matrix-cube-based estimation of distribution algorithm for the distributed assembly permutation flow-shop scheduling problem. Swarm Evol Comput 60:100785","journal-title":"Swarm Evol Comput"},{"issue":"3","key":"830_CR17","volume":"152","author":"YY Huang","year":"2020","unstructured":"Huang YY, Pan QK, Huang JP et al (2020) An improved iterated greedy algorithm for the distributed assembly permutation flowshop scheduling problem. Comput Ind Eng 152(3):107021","journal-title":"Comput Ind Eng"},{"issue":"1","key":"830_CR18","doi-asserted-by":"crossref","first-page":"4647","DOI":"10.1007\/s10489-020-01809-x","volume":"50","author":"Z Shao","year":"2020","unstructured":"Shao Z, Shao W, Pi D (2020) Effective constructive heuristic and metaheuristic for the distributed assembly blocking flow-shop scheduling problem. Appl Intell 50(1):4647\u20134669","journal-title":"Appl Intell"},{"key":"830_CR19","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1016\/j.cie.2016.07.027","volume":"99","author":"SW Lin","year":"2016","unstructured":"Lin SW, Ying KC (2016) Minimizing makespan for solving the distributed no-wait flowshop scheduling problem. Comput Ind Eng 99:202\u2013209","journal-title":"Comput Ind Eng"},{"key":"830_CR20","first-page":"1","volume":"2019","author":"W Shao","year":"2019","unstructured":"Shao W, Pi D, Shao Z (2019) A pareto-based estimation of distribution algorithm for solving multiobjective distributed no-wait flow-shop scheduling problem with sequence-dependent setup time. IEEE Trans Autom Sci Eng 2019:1\u201317","journal-title":"IEEE Trans Autom Sci Eng"},{"issue":"3","key":"830_CR21","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1007\/s11740-017-0716-9","volume":"11","author":"M Komaki","year":"2017","unstructured":"Komaki M, Malakooti B (2017) General variable neighborhood search algorithm to minimize makespan of the distributed no-wait flow shop scheduling problem. Prod Eng 11(3):315\u2013329","journal-title":"Prod Eng"},{"key":"830_CR22","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.knosys.2017.09.026","volume":"137","author":"W Shao","year":"2017","unstructured":"Shao W, Pi D, Shao Z (2017) Optimization of makespan for the distributed no-wait flow shop scheduling problem with iterated greedy algorithms. Knowl-Based Syst 137:163\u2013181","journal-title":"Knowl-Based Syst"},{"key":"830_CR23","volume":"100","author":"H Li","year":"2021","unstructured":"Li H, Li X, Gao L (2021) A discrete artificial bee colony algorithm for the distributed heterogeneous no-wait flowshop scheduling problem. Appl Soft Comput 100:106946","journal-title":"Appl Soft Comput"},{"issue":"1","key":"830_CR24","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1504\/EJIE.2017.081418","volume":"11","author":"S Behjat","year":"2017","unstructured":"Behjat S, Salmasi N (2017) Total completion time minimisation of no-wait flowshop group scheduling problem with sequence dependent setup times. Eur J Indust Eng 11(1):22","journal-title":"Eur J Indust Eng"},{"issue":"3","key":"830_CR25","doi-asserted-by":"crossref","first-page":"1143","DOI":"10.1016\/j.ejor.2006.07.029","volume":"187","author":"R Ruiz","year":"2008","unstructured":"Ruiz R, St\u00fctzle T (2008) An iterated greedy heuristic for the sequence dependent setup times flowshop problem with makespan and weighted tardiness objectives. Eur J Oper Res 187(3):1143\u20131159","journal-title":"Eur J Oper Res"},{"issue":"2","key":"830_CR26","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.ejor.2012.12.031","volume":"227","author":"M Ciavotta","year":"2013","unstructured":"Ciavotta M, Minella G, Ruiz R (2013) Multi-objective sequence dependent setup times permutation flowshop: a new algorithm and a comprehensive study. Eur J Oper Res 227(2):301\u2013313","journal-title":"Eur J Oper Res"},{"key":"830_CR27","doi-asserted-by":"crossref","first-page":"3249","DOI":"10.1016\/j.jclepro.2017.10.342","volume":"172","author":"X Wu","year":"2018","unstructured":"Wu X, Sun Y (2018) A green scheduling algorithm for flexible job shop with energy-saving measures. J Clean Prod 172:3249\u20133264","journal-title":"J Clean Prod"},{"key":"830_CR28","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2022.3145706","author":"Y Du","year":"2022","unstructured":"Du Y, Li JQ, Chen XL, Duan PY, Pan QK (2022) A knowledge-based reinforcement learning and estimation of distribution algorithm for flexible job shop scheduling problem. IEEE Trans Emerg Topics Comput Intell. https:\/\/doi.org\/10.1109\/TETCI.2022.3145706","journal-title":"IEEE Trans Emerg Topics Comput Intell"},{"issue":"3","key":"830_CR29","doi-asserted-by":"crossref","first-page":"2153","DOI":"10.1109\/TASE.2021.3062979","volume":"19","author":"JQ Li","year":"2022","unstructured":"Li JQ, Du Y, Gao KZ, Duan PY et al (2022) A hybrid iterated greedy algorithm for a crane transportation flexible job shop problem. IEEE Trans Autom Sci Eng 19(3):2153\u20132170","journal-title":"IEEE Trans Autom Sci Eng"},{"key":"830_CR30","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.ins.2022.06.056","volume":"608","author":"R Qi","year":"2022","unstructured":"Qi R, Li JQ, Wang J, Jin H, Han YYQMOEA (2022) A Q-learning-based multiobjective evolutionary algorithm for solving time-dependent green vehicle routing problems with time windows. Inf Sci 608:178\u2013201","journal-title":"Inf Sci"},{"key":"830_CR31","volume":"2020","author":"ED Jiang","year":"2020","unstructured":"Jiang ED, Wang L, Peng ZP (2020) Solving energy-efficient distributed job shop scheduling via multi-objective evolutionary algorithm with decomposition. Swarm Evol Comput 2020:100745","journal-title":"Swarm Evol Comput"},{"key":"830_CR32","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.jclepro.2018.02.004","volume":"181","author":"JQ Li","year":"2018","unstructured":"Li JQ, Sang HY, Han YY et al (2018) Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions. J Clean Prod 181:584\u2013598","journal-title":"J Clean Prod"},{"key":"830_CR33","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3128405","author":"JQ Li","year":"2021","unstructured":"Li JQ, Chen XL, Duan PY, Mou JH (2021) KMOEA: a knowledge-based multi-objective algorithm for distributed hybrid flow shop in a prefabricated system. IEEE Trans Industr Inf. https:\/\/doi.org\/10.1109\/TII.2021.3128405","journal-title":"IEEE Trans Industr Inf"},{"key":"830_CR34","volume":"50","author":"JF Chen","year":"2019","unstructured":"Chen JF, Wang L, Peng ZP (2019) A collaborative optimization algorithm for energy-efficient multi-objective distributed no-idle flow-shop scheduling. Swarm Evol Comput 50:100557","journal-title":"Swarm Evol Comput"},{"issue":"4","key":"830_CR35","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1109\/TEVC.2017.2749619","volume":"22","author":"Y Tian","year":"2018","unstructured":"Tian Y, Cheng R, Zhang XY et al (2018) An indicator-based multiobjective evolutionary algorithm with reference point adaptation for better versatility. IEEE Trans Evol Comput 22(4):609\u2013622","journal-title":"IEEE Trans Evol Comput"},{"key":"830_CR36","first-page":"1","volume":"2019","author":"H Chen","year":"2019","unstructured":"Chen H, Tian Y, Pedrycz W et al (2019) Hyperplane assisted evolutionary algorithm for many-objective optimization problems. IEEE Trans Cybern 2019:1\u201314","journal-title":"IEEE Trans Cybern"},{"key":"830_CR37","first-page":"1","volume":"000","author":"JY Ding","year":"2015","unstructured":"Ding JY, Song S, Wu C (2015) Carbon-efficient scheduling of flow shops by multi-objective optimization. Eur J Oper Res 000:1\u201314","journal-title":"Eur J Oper Res"},{"issue":"2","key":"830_CR38","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"Deb K, Pratap A, Agarwal S et al (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182\u2013197","journal-title":"IEEE Trans Evol Comput"},{"key":"830_CR39","doi-asserted-by":"crossref","DOI":"10.1016\/j.cor.2020.105204","volume":"129","author":"F Xiong","year":"2021","unstructured":"Xiong F, Chu M, Li Z et al (2021) Just-in-time scheduling for a distributed concrete precast flow shop system. Comput Oper Res 129:105204","journal-title":"Comput Oper Res"},{"issue":"1","key":"830_CR40","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0305-0483(83)90088-9","volume":"11","author":"N Muhammad","year":"1983","unstructured":"Muhammad N, Emory E, Enscore et al (1983) A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem. Omega 11(1):91\u201395","journal-title":"Omega"},{"issue":"3","key":"830_CR41","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1016\/j.ejor.2016.09.055","volume":"257","author":"V Fernandez-Viagas","year":"2017","unstructured":"Fernandez-Viagas V, Ruiz R, Framinan JM (2017) A new vision of approximate methods for the permutation flowshop to minimise makespan: state-of-the-art and computational evaluation. Eur J Oper Res 257(3):707\u2013721","journal-title":"Eur J Oper Res"},{"issue":"1","key":"830_CR42","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1109\/TCYB.2017.2771213","volume":"49","author":"Y Han","year":"2019","unstructured":"Han Y, Gong D, Jin Y et al (2019) Evolutionary multiobjective blocking lot-streaming flow shop scheduling with machine breakdowns. IEEE Trans Cybern 49(1):184\u2013197","journal-title":"IEEE Trans Cybern"},{"issue":"5","key":"830_CR43","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1016\/j.omega.2004.12.006","volume":"34","author":"R Ruiz","year":"2006","unstructured":"Ruiz R, Maroto C, Alcaraz J (2006) Two new robust genetic algorithms for the flowshop scheduling problem. Omega 34(5):461\u2013476","journal-title":"Omega"},{"issue":"3","key":"830_CR44","doi-asserted-by":"crossref","first-page":"869","DOI":"10.1016\/j.ejor.2008.04.033","volume":"196","author":"Z Yi","year":"2009","unstructured":"Yi Z, Li X, Qian W (2009) Hybrid genetic algorithm for permutation flowshop scheduling problems with total flowtime minimization. Eur J Oper Res 196(3):869\u2013876","journal-title":"Eur J Oper Res"},{"key":"830_CR45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-03315-9","volume-title":"Genetic algorithms + data structures = evolution programs","author":"Z Michalewic","year":"1996","unstructured":"Michalewic Z (1996) Genetic algorithms + data structures = evolution programs. Springer, Berlin. https:\/\/doi.org\/10.1007\/978-3-662-03315-9"},{"key":"830_CR46","first-page":"476","volume":"9771","author":"J Deng","year":"2016","unstructured":"Deng J, Wang L, Wu C et al (2016) A competitive memetic algorithm for carbon-efficient scheduling of distributed flow-shop. Int Conf Intell Comput 9771:476\u2013488 (Springer International Publishing)","journal-title":"Int Conf Intell Comput"},{"issue":"1","key":"830_CR47","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.ejor.2004.01.022","volume":"165","author":"R Ruiz","year":"2005","unstructured":"Ruiz R, Maroto C, Alcaraz J (2005) Solving the flowshop scheduling problem with sequence dependent setup times using advanced metaheuristics. Eur J Oper Res 165(1):34\u201354","journal-title":"Eur J Oper Res"},{"issue":"4","key":"830_CR48","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1109\/4235.797969","volume":"3","author":"E Zitzler","year":"1999","unstructured":"Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans Evol Comput 3(4):257\u2013271","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"830_CR49","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1007\/s10710-005-6164-x","volume":"6","author":"CAC Coello","year":"2005","unstructured":"Coello CAC, Cortes NC (2005) Solving multiobjective optimization problems using an artificial immune system. Genet Program Evolvable Mach 6(2):163\u2013190","journal-title":"Genet Program Evolvable Mach"},{"issue":"11","key":"830_CR50","doi-asserted-by":"crossref","first-page":"3234","DOI":"10.1109\/TFUZZ.2020.3016225","volume":"29","author":"JQ Li","year":"2021","unstructured":"Li JQ, Liu ZM, Li CD, Zheng ZX (2021) Improved artificial immune system algorithm for Type-2 fuzzy flexible job shop scheduling problem. IEEE Trans Fuzzy Syst 29(11):3234\u20133248","journal-title":"IEEE Trans Fuzzy Syst"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-022-00830-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-022-00830-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-022-00830-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,22]],"date-time":"2023-02-22T18:03:15Z","timestamp":1677088995000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-022-00830-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,4]]},"references-count":50,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2023,2]]}},"alternative-id":["830"],"URL":"https:\/\/doi.org\/10.1007\/s40747-022-00830-6","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,4]]},"assertion":[{"value":"24 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 July 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 August 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}