{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T21:22:28Z","timestamp":1768684948114,"version":"3.49.0"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T00:00:00Z","timestamp":1618790400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T00:00:00Z","timestamp":1618790400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61773390"],"award-info":[{"award-number":["61773390"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2022,4]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Finding the optimal size of a hybrid renewable energy system is certainly important. The problem is often modelled as an multi-objective optimization problem (MOP) in which objectives such as annualized system cost, loss of power supply probability etc. are minimized. However, the MOP model rarely takes the load characteristics into account. We argue that ignoring load characteristics may be inappropriate when designing HRES for a place with intermittent high load demand. For example, in a training base the load demand is high when there are training tasks while the demand decreases to a low level when there is no training task. This results in an interesting issue, that is, when the loss of power supply probability is determined at a specific value, say 15%, then it is very likely that most of loss of power supply would occur right in the training period which is unexpected. Therefore, this study proposes a constraint multi-objective model to deal with this issue\u2014in addition to the general multi-objective optimization model, the loss of power supply probability over a critical period is set as a constraint. Correspondingly, the non-dominated sorting genetic algorithm II with a relaxed <jats:inline-formula><jats:alternatives><jats:tex-math>$$\\epsilon $$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mi>\u03f5<\/mml:mi>\n                <\/mml:math><\/jats:alternatives><\/jats:inline-formula> constraint handling strategy is proposed to address the constraint MOP. Experimental results on a real world application demonstrate that the proposed model and algorithm are both effective and efficient.<\/jats:p>","DOI":"10.1007\/s40747-021-00363-4","type":"journal-article","created":{"date-parts":[[2021,4,19]],"date-time":"2021-04-19T20:03:50Z","timestamp":1618862630000},"page":"803-817","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":31,"title":["Constraint multi-objective optimal design of hybrid renewable energy system considering load characteristics"],"prefix":"10.1007","volume":"8","author":[{"given":"Yingfeng","family":"Chen","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9048-2979","authenticated-orcid":false,"given":"Rui","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Mengjun","family":"Ming","sequence":"additional","affiliation":[]},{"given":"Shi","family":"Cheng","sequence":"additional","affiliation":[]},{"given":"Yiping","family":"Bao","sequence":"additional","affiliation":[]},{"given":"Wensheng","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Chi","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,19]]},"reference":[{"key":"363_CR1","doi-asserted-by":"crossref","unstructured":"Hongxing Wei Z, Chengzhi L (2009) Optimal design and techno-economic analysis of a hybrid solar-wind power generation system. Appl Energy 86(2):163\u2013169 (IGEC III)","DOI":"10.1016\/j.apenergy.2008.03.008"},{"key":"363_CR2","doi-asserted-by":"publisher","first-page":"376","DOI":"10.1016\/j.rser.2015.12.281","volume":"58","author":"R Siddaiah","year":"2016","unstructured":"Siddaiah R, Saini RP (2016) A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications. Renew Sustain Energy Rev 58:376\u2013396","journal-title":"Renew Sustain Energy Rev"},{"key":"363_CR3","doi-asserted-by":"publisher","first-page":"2288","DOI":"10.1016\/j.energy.2017.11.085","volume":"141","author":"R Wang","year":"2017","unstructured":"Wang R, Li G, Ming M, Wu G, Wang L (2017) An efficient multi-objective model and algorithm for sizing a stand-alone hybrid renewable energy system. Energy 141:2288\u20132299","journal-title":"Energy"},{"key":"363_CR4","doi-asserted-by":"crossref","unstructured":"Fonseca C, Fleming P (1998) Multiobjective optimization and multiple constraint handling with evolutionary algorithms. I. A unified formulation. IEEE Trans Syst Man Cybern Part A Syst Hum 28(1):26\u201337","DOI":"10.1109\/3468.650319"},{"issue":"2","key":"363_CR5","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1016\/j.ins.2013.08.049","volume":"258","author":"R Wang","year":"2014","unstructured":"Wang R, Fleming P, Purshouse R (2014) General framework for localised multi-objective evolutionary algorithms. Inform Sci 258(2):29\u201353","journal-title":"Inform Sci"},{"issue":"1","key":"363_CR6","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1109\/TEVC.2016.2611642","volume":"22","author":"R Wang","year":"2018","unstructured":"Wang R, Ishibuchi H, Zhou Z, Liao T, Zhang T (2018) Localized weighted sum method for many-objective optimization. IEEE Trans Evolut Comput 22(1):3\u201318","journal-title":"IEEE Trans Evolut Comput"},{"key":"363_CR7","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1016\/j.enconman.2017.04.019","volume":"143","author":"MD Al-falahi","year":"2017","unstructured":"Al-falahi MD, Jayasinghe S, Enshaei H (2017) A review on recent size optimization methodologies for standalone solar and wind hybrid renewable energy system. Energy Conv Manag 143:252\u2013274","journal-title":"Energy Conv Manag"},{"issue":"4","key":"363_CR8","doi-asserted-by":"publisher","first-page":"591","DOI":"10.1007\/s11708-018-0567-x","volume":"12","author":"M Faccio","year":"2018","unstructured":"Faccio M, Gamberi M, Bortolini M, Nedaei M (2018) State-of-art review of the optimization methods to design the configuration of hybrid renewable energy systems (hress). Front Energy 12(4):591\u2013622","journal-title":"Front Energy"},{"key":"363_CR9","doi-asserted-by":"crossref","unstructured":"Lian J, Zhang Y, Ma C, Yang Y, Chaima E (2019) A review on recent sizing methodologies of hybrid renewable energy systems. Energy Conv Manag 199","DOI":"10.1016\/j.enconman.2019.112027"},{"issue":"2","key":"363_CR10","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.apenergy.2008.03.008","volume":"86","author":"H Yang","year":"2009","unstructured":"Yang H, Wei Z, Lou C (2009) Optimal design and techno-economic analysis of a hybrid solar-wind power generation system. Appl Energy 86(2):163\u2013169","journal-title":"Appl Energy"},{"key":"363_CR11","doi-asserted-by":"publisher","first-page":"640","DOI":"10.1016\/j.apenergy.2017.12.040","volume":"212","author":"AS Jacob","year":"2018","unstructured":"Jacob AS, Banerjee R, Ghosh PC (2018) Sizing of hybrid energy storage system for a pv based microgrid through design space approach. Appl Energy 212:640\u2013653","journal-title":"Appl Energy"},{"key":"363_CR12","doi-asserted-by":"publisher","first-page":"1453","DOI":"10.1016\/j.enconman.2019.06.085","volume":"196","author":"M Elkadeem","year":"2019","unstructured":"Elkadeem M, Wang S, Sharshir SW, Atia EG (2019) Feasibility analysis and techno-economic design of grid-isolated hybrid renewable energy system for electrification of agriculture and irrigation area: A case study in dongola, sudan. Energy Conv Manag 196:1453\u20131478","journal-title":"Energy Conv Manag"},{"key":"363_CR13","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1016\/j.renene.2017.11.058","volume":"119","author":"Y Sawle","year":"2018","unstructured":"Sawle Y, Gupta S, Bohre AK (2018) Socio-techno-economic design of hybrid renewable energy system using optimization techniques. Renew Energy 119:459\u2013472","journal-title":"Renew Energy"},{"key":"363_CR14","doi-asserted-by":"publisher","first-page":"941","DOI":"10.1016\/j.solener.2017.10.040","volume":"158","author":"A Yahiaoui","year":"2017","unstructured":"Yahiaoui A, Fodhil F, Benmansour K, Tadjine M, Cheggaga N (2017) Grey wolf optimizer for optimal design of hybrid renewable energy system pv-diesel generator-battery: application to the case of djanet city of algeria. Solar Energy 158:941\u2013951","journal-title":"Solar Energy"},{"key":"363_CR15","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1016\/j.enconman.2018.07.083","volume":"173","author":"AM Abdelshafy","year":"2018","unstructured":"Abdelshafy AM, Hassan H, Jurasz J (2018) Optimal design of a grid-connected desalination plant powered by renewable energy resources using a hybrid pso-gwo approach. Energy Conv Manag 173:331\u2013347","journal-title":"Energy Conv Manag"},{"key":"363_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.scs.2018.05.002","volume":"41","author":"Z Movahediyan","year":"2018","unstructured":"Movahediyan Z, Askarzadeh A (2018) Multi-objective optimization framework of a photovoltaic-diesel generator hybrid energy system considering operating reserve. Sustain Cities Soc 41:1\u201312","journal-title":"Sustain Cities Soc"},{"key":"363_CR17","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.enconman.2019.04.064","volume":"193","author":"A Kaabeche","year":"2019","unstructured":"Kaabeche A, Bakelli Y (2019) Renewable hybrid system size optimization considering various electrochemical energy storage technologies. Energy Conv Manag 193:162\u2013175","journal-title":"Energy Conv Manag"},{"key":"363_CR18","doi-asserted-by":"publisher","first-page":"920","DOI":"10.1016\/j.enconman.2019.05.078","volume":"196","author":"K Lee","year":"2019","unstructured":"Lee K, Kum D (2019) Complete design space exploration of isolated hybrid renewable energy system via dynamic programming. Energy Conv Manag 196:920\u2013934","journal-title":"Energy Conv Manag"},{"key":"363_CR19","doi-asserted-by":"publisher","first-page":"909","DOI":"10.1016\/j.enconman.2016.08.061","volume":"126","author":"H Zahboune","year":"2016","unstructured":"Zahboune H, Zouggar S, Krajacic G, Varbanov PS, Elhafyani M, Ziani E (2016) Optimal hybrid renewable energy design in autonomous system using modified electric system cascade analysis and homer software. Energy Conv Manag 126:909\u2013922","journal-title":"Energy Conv Manag"},{"key":"363_CR20","doi-asserted-by":"publisher","first-page":"1068","DOI":"10.1016\/j.solener.2019.07.008","volume":"188","author":"K Murugaperumal","year":"2019","unstructured":"Murugaperumal K, Raj PADV (2019) Feasibility design and techno-economic analysis of hybrid renewable energy system for rural electrification. Solar Energy 188:1068\u20131083","journal-title":"Solar Energy"},{"key":"363_CR21","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.apenergy.2018.04.032","volume":"223","author":"JJ Roberts","year":"2018","unstructured":"Roberts JJ, Cassula AM, Silveira JL, da Costa Bortoni E, Mendiburu AZ (2018) Robust multi-objective optimization of a renewable based hybrid power system. Appl Energy 223:52\u201368","journal-title":"Appl Energy"},{"issue":"1","key":"363_CR22","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/j.ijepes.2015.07.007","volume":"74","author":"A Kamjoo","year":"2016","unstructured":"Kamjoo A, Maheri A, Dizqah AM, Putrus GA (2016) Multi-objective design under uncertainties of hybrid renewable energy system using NSGA-II and chance constrained programming. Int J Elect Power Energy Syst 74(1):187\u2013C194","journal-title":"Int J Elect Power Energy Syst"},{"key":"363_CR23","doi-asserted-by":"publisher","first-page":"514","DOI":"10.1016\/j.ijepes.2016.04.008","volume":"83","author":"A Maleki","year":"2016","unstructured":"Maleki A, Khajeh MG, Ameri M (2016) Optimal sizing of a grid independent hybrid renewable energy system incorporating resource uncertainty, and load uncertainty. Int J Elect Power Energy Syst 83:514\u2013524","journal-title":"Int J Elect Power Energy Syst"},{"key":"363_CR24","doi-asserted-by":"crossref","unstructured":"Wang W, Peng Y, Li X, Qi Q, Feng P, Zhang Y (2019) A two-stage framework for the optimal design of a hybrid renewable energy system for port application. Ocean Eng 191","DOI":"10.1016\/j.oceaneng.2019.106555"},{"issue":"11","key":"363_CR25","doi-asserted-by":"publisher","first-page":"4033","DOI":"10.1016\/j.apenergy.2011.04.019","volume":"88","author":"R Dufo-L\u00f3pez","year":"2011","unstructured":"Dufo-L\u00f3pez R, Bernal-Agust\u00edn JL, Yusta-Loyo JM, Dom\u00ednguez-Navarro JA, Ram\u00edrez-Rosado IJ, Lujano J et al (2011) Multi-objective optimization minimizing cost and life cycle emissions of stand-alone pv-wind-diesel systems with batteries storage. Appl Energy 88(11):4033\u20134041","journal-title":"Appl Energy"},{"issue":"3","key":"363_CR26","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1016\/j.rser.2011.11.030","volume":"16","author":"S Abedi","year":"2012","unstructured":"Abedi S, Alimardani A, Gharehpetian G, Riahy G, Hosseinian S (2012) A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems. Renew Sustain Energy Rev 16(3):1577\u20131587","journal-title":"Renew Sustain Energy Rev"},{"issue":"1","key":"363_CR27","doi-asserted-by":"publisher","first-page":"1668","DOI":"10.1016\/j.rser.2015.08.010","volume":"52","author":"M Sharafi","year":"2015","unstructured":"Sharafi M, Elmekkawy TY (2015) Stochastic optimization of hybrid renewable energy systems using sampling average method. Renew Sustain Energy Rev 52(1):1668\u20131679","journal-title":"Renew Sustain Energy Rev"},{"issue":"12","key":"363_CR28","doi-asserted-by":"publisher","first-page":"2559","DOI":"10.1016\/j.renene.2008.02.027","volume":"33","author":"R Dufo-L\u00f3pez","year":"2008","unstructured":"Dufo-L\u00f3pez R, Bernal-Agust\u00edn JL (2008) Multi-objective design of PV-wind-diesel-hydrogen-battery systems. Renew Energy 33(12):2559\u20132572","journal-title":"Renew Energy"},{"key":"363_CR29","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1016\/j.solener.2015.03.052","volume":"118","author":"Z Shi","year":"2015","unstructured":"Shi Z, Wang R, Zhang T (2015) Multi-objective optimal design of hybrid renewable energy systems using preference-inspired coevolutionary approach. Solar Energy 118:96\u2013106","journal-title":"Solar Energy"},{"issue":"4","key":"363_CR30","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1109\/TEVC.2012.2204264","volume":"17","author":"R Wang","year":"2013","unstructured":"Wang R, Purshouse RC, Fleming PJ (2013) Preference-inspired co-evolutionary algorithms for many-objective optimisation. IEEE Trans Evolut Comput 17(4):474\u2013494","journal-title":"IEEE Trans Evolut Comput"},{"issue":"4","key":"363_CR31","doi-asserted-by":"publisher","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 Evolut Comput 3(4):257\u2013271","journal-title":"IEEE Trans Evolut Comput"},{"issue":"2","key":"363_CR32","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, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evolut Comput 6(2):182\u2013197","journal-title":"IEEE Trans Evolut Comput"},{"issue":"6","key":"363_CR33","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","volume":"11","author":"Q Zhang","year":"2007","unstructured":"Zhang Q, Li H (2007) MOEA\/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evolut Comput 11(6):712\u2013731","journal-title":"IEEE Trans Evolut Comput"},{"issue":"6","key":"363_CR34","doi-asserted-by":"publisher","first-page":"821","DOI":"10.1109\/TEVC.2016.2521175","volume":"20","author":"R Wang","year":"2016","unstructured":"Wang R, Zhang Q, Zhang T (2016) Decomposition based algorithms using Pareto adaptive scalarizing methods. IEEE Trans Evolut Comput 20(6):821\u2013837","journal-title":"IEEE Trans Evolut Comput"},{"key":"363_CR35","doi-asserted-by":"crossref","unstructured":"Wang, R., Zhang, F., Zhang, T.. Multi-objective optimal design of hybrid renewable energy systems using evolutionary algorithms. In: Natural Computation (ICNC), 2015 11th International Conference on. IEEE; 2015a, p. 1196\u20131200","DOI":"10.1109\/ICNC.2015.7378161"},{"key":"363_CR36","unstructured":"Fan Z, Li W, Cai X, Huang H, Fang Y, You Y, et al (2017) An improved epsilon constraint-handling method in MOEA\/D for CMOPs with large infeasible regions. Soft Comput: 1\u201320"},{"issue":"2","key":"363_CR37","first-page":"115","volume":"9","author":"RB Agrawal","year":"1995","unstructured":"Agrawal RB, Deb K, Agrawal R (1995) Simulated binary crossover for continuous search space. Complex Syst 9(2):115\u2013148","journal-title":"Complex Syst"},{"issue":"13","key":"363_CR38","first-page":"423","volume":"46","author":"R Wang","year":"2015","unstructured":"Wang R, Mansor MM, Purshouse RC, Fleming PJ (2015b) An analysis of parameter sensitivities of preference-inspired co-evolutionary algorithms. Int J Syst Sci 46(13):423\u2013441","journal-title":"Int J Syst Sci"},{"key":"363_CR39","doi-asserted-by":"publisher","first-page":"770","DOI":"10.1109\/TEVC.2007.910138","volume":"11","author":"RC Purshouse","year":"2007","unstructured":"Purshouse RC, Fleming PJ (2007) On the evolutionary optimization of many conflicting objectives. IEEE Trans Evolut Comput 11:770\u2013784","journal-title":"IEEE Trans Evolut Comput"},{"key":"363_CR40","doi-asserted-by":"crossref","unstructured":"Bernal-Agust\u0301n JL, Dufo-L\u00f3pez R (2009) Efficient design of hybrid renewable energy systems using evolutionary algorithms. Energy Conv Manag 50(3):479\u2013489","DOI":"10.1016\/j.enconman.2008.11.007"},{"key":"363_CR41","doi-asserted-by":"crossref","unstructured":"Li G, Wang R, Zhang T, Ming M (2018) Multi-objective optimal design of renewable energy integrated cchp system using picea-g. Energies 11(743)","DOI":"10.3390\/en11040743"},{"issue":"3","key":"363_CR42","first-page":"479","volume":"24","author":"F Wang","year":"2020","unstructured":"Wang F, Li Y, Zhou A, Tang K (2020) An estimation of distribution algorithm for mixed-variable newsvendor problems. IEEE Trans Evolut Comput 24(3):479\u2013493","journal-title":"IEEE Trans Evolut Comput"},{"key":"363_CR43","doi-asserted-by":"crossref","unstructured":"Wang F, Zhang H, Zhou A (2021) A particle swarm optimization algorithm for mixed-variable optimization problems. Swarm Evolut Comput 60","DOI":"10.1016\/j.swevo.2020.100808"},{"key":"363_CR44","doi-asserted-by":"crossref","unstructured":"Mallipeddi R, Suganthan PN (2010) Ensemble of constraint handling techniques. IEEE Trans Evolut Comput 14(4):561\u2013579","DOI":"10.1109\/TEVC.2009.2033582"},{"key":"363_CR45","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1016\/j.ins.2017.09.053","volume":"423","author":"G Wu","year":"2018","unstructured":"Wu G, Shen X, Li H, Chen H, Lin A, Suganthan P (2018) Ensemble of differential evolution variants. Inform Sci 423:172\u2013186","journal-title":"Inform Sci"},{"issue":"7","key":"363_CR46","doi-asserted-by":"publisher","first-page":"6335","DOI":"10.1016\/j.eswa.2011.12.017","volume":"39","author":"B Wu","year":"2012","unstructured":"Wu B, Qian C, Ni W, Fan S (2012) The improvement of glowworm swarm optimization for continuous optimization problems. Expert Syst Appl 39(7):6335\u20136342","journal-title":"Expert Syst Appl"},{"issue":"4","key":"363_CR47","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1016\/j.solener.2013.05.007","volume":"94","author":"W Gong","year":"2013","unstructured":"Gong W, Cai Z (2013) Parameter extraction of solar cell models using repaired adaptive differential evolution. Solar Energy 94(4):209\u2013220","journal-title":"Solar Energy"},{"issue":"5","key":"363_CR48","doi-asserted-by":"publisher","first-page":"746","DOI":"10.1109\/TEVC.2015.2449293","volume":"19","author":"W Gong","year":"2015","unstructured":"Gong W, Zhou A, Cai Z (2015) A multioperator search strategy based on cheap surrogate models for evolutionary optimization. IEEE Trans Evolut Comput 19(5):746\u2013758","journal-title":"IEEE Trans Evolut Comput"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-021-00363-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-021-00363-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-021-00363-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,29]],"date-time":"2022-04-29T17:30:59Z","timestamp":1651253459000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-021-00363-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,19]]},"references-count":48,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,4]]}},"alternative-id":["363"],"URL":"https:\/\/doi.org\/10.1007\/s40747-021-00363-4","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,19]]},"assertion":[{"value":"11 December 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 March 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 April 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declaration"}},{"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"}}]}}