{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T12:19:02Z","timestamp":1766578742101,"version":"3.37.3"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T00:00:00Z","timestamp":1650844800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T00:00:00Z","timestamp":1650844800000},"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":["72101266"],"award-info":[{"award-number":["72101266"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Military Postgraduate Funding Project","award":["JY2019C055"],"award-info":[{"award-number":["JY2019C055"]}]},{"name":"Hunan Province Postgraduate Scientific Research Innovation Project","award":["CX20200029"],"award-info":[{"award-number":["CX20200029"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Electronic countermeasure (ECM) has become one of the most significant factors in modern warfare, in the course of combat, the electronic jamming allocation tasks need to be flexibly adjusted with the change of combat stage, which puts forward higher requirements for the modeling and solution method of this kind of problems. To solve the ECM dynamic weapon target assignment (ECM-DWTA) problem, a hybrid multi-target bi-level programming model is established. The upper level takes the sum of the electronic jamming effects in the whole combat stage as an optimization objective, and locally optimizes the ECM weapon (ECM-WP) assignment scheme in each stage. The lower level takes the importance expectation value of the target subjected to interference and combat consumption as double optimization objectives to globally optimize the ECM-WP assignment scheme. Focus on solving this complex model, a hybrid multi-objective bi-level interactive fuzzy programming algorithm (HMOBIF) is proposed, in this method, exponential membership function is used to describe the satisfaction degree of each level. When solving the multi-objective optimization problem composed of membership functions in the upper and lower levels, we use the MOEA\/D algorithm to obtain the Pareto Front (PF) solution set, and then each solution in PF is evaluated and selected by the TOPSIS multi-criteria evaluation method. This local and global interactive optimization process of bi-level model is actually the process of executing observation-orientation-decision-action loop in practical combat. According to the current example, we conduct numerical simulation on the parameters in the model and obtain the parameter values suitable for the model solution. The computational experiments on different scale ECM-DWTA problems show that HMOBIF method is superior to four bi-level programming algorithms in terms of performance index, and can better solve ECM-DWTA problems.<\/jats:p>","DOI":"10.1007\/s40747-022-00730-9","type":"journal-article","created":{"date-parts":[[2022,4,25]],"date-time":"2022-04-25T05:02:57Z","timestamp":1650862977000},"page":"4811-4829","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["A hybrid multi-objective bi-level interactive fuzzy programming method for solving ECM-DWTA problem"],"prefix":"10.1007","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7476-5896","authenticated-orcid":false,"given":"Luda","family":"Zhao","sequence":"first","affiliation":[]},{"given":"Zongxu","family":"An","sequence":"additional","affiliation":[]},{"given":"Bin","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Yanqiu","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yihua","family":"Hu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,4,25]]},"reference":[{"key":"730_CR1","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1016\/j.cie.2019.01.015","volume":"128","author":"MF Hocaolu","year":"2019","unstructured":"Hocaolu MF (2019) Weapon target assignment optimization for land based multi-air defense systems: a goal programming approach. Comput Ind Eng 128:681\u2013689","journal-title":"Comput Ind Eng"},{"key":"730_CR2","doi-asserted-by":"publisher","first-page":"105542","DOI":"10.1016\/j.asoc.2019.105542","volume":"82","author":"CM Lai","year":"2019","unstructured":"Lai CM, Wu TH (2019) Simplified swarm optimization with initialization scheme for dynamic weapon target assignment problem. Appl Soft Comput 82:105542","journal-title":"Appl Soft Comput"},{"key":"730_CR3","doi-asserted-by":"crossref","unstructured":"Lu X, Di H, Jia Z, Zhang X (2019) Optimal weapon target assignment based on improved QPSO algorithm. In: 2019 international conference on information technology and computer application (ITCA). pp 217\u2013220","DOI":"10.1109\/ITCA49981.2019.00054"},{"issue":"2","key":"730_CR4","doi-asserted-by":"publisher","first-page":"172988142090592","DOI":"10.1177\/1729881420905922","volume":"17","author":"Y Zhao","year":"2020","unstructured":"Zhao Y, Chen Y, Zhen Z, Jiang J (2020) Multi-weapon multi-target assignment based on hybrid genetic algorithm in uncertain environment. Int J Adv Robot Syst 17(2):1729881420905922","journal-title":"Int J Adv Robot Syst"},{"key":"730_CR5","doi-asserted-by":"crossref","unstructured":"Chen Z, Liang Z, Dong X, Li Q, Ren Z (2019) Adaptive weapon-target assignment for multi-target interception. In: 2019 Chinese control conference (CCC). pp 4218\u20134223","DOI":"10.23919\/ChiCC.2019.8865884"},{"key":"730_CR6","doi-asserted-by":"publisher","first-page":"112844","DOI":"10.1016\/j.eswa.2019.112844","volume":"140","author":"W Xu","year":"2020","unstructured":"Xu W, Chen C, Ding S, Pardalos PM (2020) A bi-objective dynamic collaborative task assignment under uncertainty using modified MOEA\/D with heuristic initialization. Expert Syst Appl 140:112844","journal-title":"Expert Syst Appl"},{"issue":"11","key":"730_CR7","first-page":"1886","volume":"36","author":"YP Wang","year":"2019","unstructured":"Wang YP, Xin B, Chen J (2019) Modeling and optimization of multi-stage sensor-weapon-target assignment. Control Theory Appl 36(11):1886\u20131895","journal-title":"Control Theory Appl"},{"issue":"18","key":"730_CR8","doi-asserted-by":"publisher","first-page":"3803","DOI":"10.3390\/app9183803","volume":"9","author":"X Li","year":"2019","unstructured":"Li X, Zhou D, Yang Z, Pan Q, Huang J (2019) A novel genetic algorithm for the synthetical sensor-weapon-target assignment problem. Appl Sci 9(18):3803","journal-title":"Appl Sci"},{"issue":"3","key":"730_CR9","doi-asserted-by":"publisher","first-page":"539","DOI":"10.23919\/JSEE.2020.000033","volume":"31","author":"ZR Jia","year":"2020","unstructured":"Jia ZR, Lu FX, Wang HY (2020) Multi-stage attack weapon target allocation method based on defense area analysis. J Syst Eng Electron 31(3):539\u2013550","journal-title":"J Syst Eng Electron"},{"issue":"2","key":"730_CR10","first-page":"185","volume":"41","author":"XJ Zhang","year":"2019","unstructured":"Zhang XJ (2019) Land defense weapon versus target assignment against air attack. J Natl Univ Defense Technol 41(2):185\u2013190","journal-title":"J Natl Univ Defense Technol"},{"issue":"9","key":"730_CR11","first-page":"1941","volume":"32","author":"F Ma","year":"2010","unstructured":"Ma F, Cao ZY, Liu H (2010) Construction and search of strategy space of target assignment based on game theory. Syst Eng Electron 32(9):1941\u20131945","journal-title":"Syst Eng Electron"},{"key":"730_CR12","first-page":"26","volume":"38","author":"Y Zhang","year":"2012","unstructured":"Zhang Y, Jiang QS, Chen GS (2012) An approach of basing-on fuzzy-grey noncooperative Nash games to multi-team dynamic weapon-target assignment. J Yunnan Univ (Natural Science) 38:26\u201332","journal-title":"J Yunnan Univ (Natural Science)"},{"issue":"4","key":"730_CR13","first-page":"53","volume":"24","author":"HS Uhm","year":"2019","unstructured":"Uhm HS, Lee YH (2019) An approach of basing-on fuzzy-grey noncooperative Nash games to multi-team dynamic weapon-target assignment. Mil Oper Res 24(4):53\u201362","journal-title":"Mil Oper Res"},{"key":"730_CR14","unstructured":"Shin MK, Lee D, Choi HL (2019) Weapon-target assignment problem with interference constraints using mixed-integer linear programming. arXiv preprint arXiv:1911:12567"},{"issue":"2","key":"730_CR15","doi-asserted-by":"publisher","first-page":"188","DOI":"10.11121\/ijocta.01.2020.00775","volume":"10","author":"E Sonu","year":"2019","unstructured":"Sonu E (2019) A modified crow search algorithm for the weapon-target assignment problem. Int J Optim Control Theor Appl (IJOCTA) 10(2):188\u2013197","journal-title":"Int J Optim Control Theor Appl (IJOCTA)"},{"issue":"1","key":"730_CR16","doi-asserted-by":"publisher","first-page":"012001","DOI":"10.1088\/1742-6596\/1419\/1\/012001","volume":"1419","author":"H Jiang","year":"2019","unstructured":"Jiang H, Li S, Lin C, Wang C, Zhong K, He G, Zhang QZ, Zhao YH, Liu J (2019) Research on distributed target assignment based on dynamic allocation auction algorithm. J Phys Conf Ser 1419(1):012001","journal-title":"J Phys Conf Ser"},{"issue":"1","key":"730_CR17","doi-asserted-by":"publisher","first-page":"012062","DOI":"10.1088\/1742-6596\/1651\/1\/012062","volume":"1651","author":"K Zhang","year":"2020","unstructured":"Zhang K, Zhou D, Yang Z, Li X, Zhao Y, Kong W (2020) A dynamic weapon target assignment based on receding horizon strategy by heuristic algorithm. J Phys Conf Ser 1651(1):012062","journal-title":"J Phys Conf Ser"},{"issue":"9","key":"730_CR18","doi-asserted-by":"publisher","first-page":"1511","DOI":"10.3390\/electronics9091511","volume":"9","author":"K Zhang","year":"2019","unstructured":"Zhang K, Zhou D, Yang Z, Zhao Y, Kong W (2019) Efficient decision approaches for asset-based dynamic weapon target assignment by a receding horizon and marginal return heuristic. Electronics 9(9):1511","journal-title":"Electronics"},{"key":"730_CR19","doi-asserted-by":"crossref","unstructured":"Li J, Chen J, Xin B, Dou L, Peng Z (2016) Solving the uncertain multi-objective multi-stage weapon target assignment problem via MOEA\/D-AWA. In: Proceedings of the 2016 IEEE congress on evolutionary computation (CEC). pp 4934\u20134941","DOI":"10.1109\/CEC.2016.7744423"},{"key":"730_CR20","doi-asserted-by":"crossref","unstructured":"Li J, Chen J, Xin B, Dou L (2015) Solving multi-objective multi-stage weapon target assignment problem via adaptive NSGA-II and adaptive MOEA\/D: a comparison study. In Proceedings of the 2015 IEEE congress on evolutionary computation (CEC). pp 3132\u20133139","DOI":"10.1109\/CEC.2015.7257280"},{"key":"730_CR21","doi-asserted-by":"crossref","unstructured":"Zou S, Shi X, Guo R, Lin X (2020) Solving multi-stage weapon target assignment problems by C-TAEA. In 2020 39th Chinese control conference (CCC). pp 1593\u20131598","DOI":"10.23919\/CCC50068.2020.9188559"},{"key":"730_CR22","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1016\/j.automatica.2019.03.007","volume":"105","author":"G Qu","year":"2019","unstructured":"Qu G, Brown D, Li N (2019) Distributed greedy algorithm for multi-agent task assignment problem with submodular utility functions. Automatica 105:206\u2013215","journal-title":"Automatica"},{"issue":"3","key":"730_CR23","doi-asserted-by":"publisher","first-page":"3045","DOI":"10.1007\/s11063-019-10068-y","volume":"50","author":"A Shojaeifard","year":"2019","unstructured":"Shojaeifard A, Amroudi AN, Mansoori A, Erfanian M (2019) Projection recurrent neural network model: a new strategy to solve weapon-target assignment problem. Neural Process Lett 50(3):3045\u20133057","journal-title":"Neural Process Lett"},{"key":"730_CR24","doi-asserted-by":"publisher","first-page":"72210","DOI":"10.1109\/ACCESS.2019.2919794","volume":"7","author":"J Jang","year":"2019","unstructured":"Jang J, Yoon HG, Kim JC, Kim CO (2019) Adaptive weapon-to-target assignment model based on the real-time prediction of hit probability. IEEE Access 7:72210\u201372220","journal-title":"IEEE Access"},{"key":"730_CR25","first-page":"59","volume":"11","author":"B Hu","year":"2014","unstructured":"Hu B, Hou L (2014) Research and simulation of communication jamming task assignment optimization based on bi-level stochastic chance-constraint programming. Fire Control Command Control 11:59\u201363","journal-title":"Fire Control Command Control"},{"issue":"2","key":"730_CR26","first-page":"85","volume":"39","author":"CW Xiang","year":"2017","unstructured":"Xiang CW, Jiang QS, Qu Z (2017) Modeling and algorithm of dynamic resource assignment for ESJ electronic warfare aircraft. Command Control Simul 39(2):85\u201389","journal-title":"Command Control Simul"},{"issue":"1","key":"730_CR27","first-page":"3","volume":"17","author":"O Castillo","year":"2018","unstructured":"Castillo O (2018) Towards finding the optimal n in designing Type-n Fuzzy systems for particular classes of problems: a review. Appl Comput Math 17(1):3\u20139","journal-title":"Appl Comput Math"},{"key":"730_CR28","unstructured":"Lloyd SP, Witsenhausen HS (1986) Weapons allocation is NP-complete. In: Proceedings of the 1986 summer computer simulation conference. pp 1054\u20131058"},{"issue":"2","key":"730_CR29","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1016\/S0377-2217(96)00335-9","volume":"99","author":"MG Nicholls","year":"1997","unstructured":"Nicholls MG (1997) Developing an integrated model of an aluminium smelter incorporating sub-models with different time bases and levels of aggregation. Eur J Oper Res 99(2):477\u2013490","journal-title":"Eur J Oper Res"},{"issue":"8","key":"730_CR30","doi-asserted-by":"publisher","first-page":"1004","DOI":"10.1287\/mnsc.30.8.1004","volume":"30","author":"WF Bialas","year":"1984","unstructured":"Bialas WF, Karwan MH (1984) Two-level linear programming. Manag Sci 30(8):1004\u20131020","journal-title":"Manag Sci"},{"issue":"1","key":"730_CR31","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1007\/BF02098176","volume":"34","author":"FA Al-Khayyal","year":"1992","unstructured":"Al-Khayyal FA, Horst R, Pardalos PM (1992) Global optimization of concave functions subject to quadratic constraints: an application in nonlinear bilevel programming. Ann Oper Res 34(1):125\u2013147","journal-title":"Ann Oper Res"},{"issue":"3","key":"730_CR32","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1007\/s10589-015-9795-8","volume":"63","author":"S Dempe","year":"2016","unstructured":"Dempe S, Franke S (2016) On the solution of convex bilevel optimization problems. Comput Optim Appl 63(3):685\u2013703","journal-title":"Comput Optim Appl"},{"issue":"5","key":"730_CR33","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1016\/0167-6377(94)90086-8","volume":"15","author":"G Savard","year":"1994","unstructured":"Savard G, Gauvin J (1994) The steepest descent direction for the nonlinear bilevel programming problem. Oper Res Lett 15(5):265\u2013272","journal-title":"Oper Res Lett"},{"issue":"3","key":"730_CR34","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s10589-005-4612-4","volume":"30","author":"B Colson","year":"2005","unstructured":"Colson B, Marcotte P, Savard G (2005) A trust-region method for nonlinear bilevel programming: algorithm and computational experience. Comput Optim Appl 30(3):211\u2013227","journal-title":"Comput Optim Appl"},{"key":"730_CR35","doi-asserted-by":"crossref","unstructured":"Sinha A, Malo P, Deb K (2017) A review on bilevel optimization: from classical to evolutionary approaches and applications. IEEE Trans Evol Comput 22(2):276\u2013295","DOI":"10.1109\/TEVC.2017.2712906"},{"issue":"13","key":"730_CR36","doi-asserted-by":"publisher","first-page":"3136","DOI":"10.1016\/j.apm.2013.11.008","volume":"38","author":"Y Zheng","year":"2014","unstructured":"Zheng Y, Liu J, Wan Z (2014) Interactive fuzzy decision making method for solving bilevel programming problem. Appl Math Model 38(13):3136\u20133141","journal-title":"Appl Math Model"},{"key":"730_CR37","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1007\/s40305-018-0234-2","volume":"9","author":"SK Maiti","year":"2021","unstructured":"Maiti SK, Roy SK (2021) Bi-level programming for Stackelberg game with intuitionistic fuzzy number: a ranking approach. J Oper Res Soc China 9:131\u2013149","journal-title":"J Oper Res Soc China"},{"issue":"2","key":"730_CR38","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1109\/91.842154","volume":"8","author":"Y Jin","year":"2000","unstructured":"Jin Y (2000) Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement. IEEE Trans Fuzzy Syst 8(2):212\u2013221","journal-title":"IEEE Trans Fuzzy Syst"},{"key":"730_CR39","doi-asserted-by":"crossref","unstructured":"Castillo O, Melin P, Kacprzyk J, Pedrycz W (2007) Type-2 fuzzy logic: theory and applications. In: 2007 IEEE international conference on granular computing (GRC 2007). pp 145\u2013145","DOI":"10.1109\/GrC.2007.118"},{"key":"730_CR40","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1016\/j.asoc.2017.03.048","volume":"57","author":"L Rodr\u00edguez","year":"2017","unstructured":"Rodr\u00edguez L, Castillo O, Soria J et al (2017) A fuzzy hierarchical operator in the grey wolf optimizer algorithm. Appl Soft Comput 57:315\u2013328","journal-title":"Appl Soft Comput"},{"issue":"3","key":"730_CR41","doi-asserted-by":"publisher","first-page":"701","DOI":"10.1007\/s40815-017-0443-6","volume":"20","author":"J Soto","year":"2018","unstructured":"Soto J, Melin P, Castillo O (2018) A new approach for time series prediction using ensembles of IT2FNN models with optimization of fuzzy integrators. Int J Fuzzy Syst 20(3):701\u2013728","journal-title":"Int J Fuzzy Syst"},{"issue":"1","key":"730_CR42","doi-asserted-by":"publisher","first-page":"42","DOI":"10.1007\/s40815-020-00976-w","volume":"23","author":"E Bernal","year":"2021","unstructured":"Bernal E, Lagunes ML, Castillo O, Soria J, Valdez F (2021) Optimization of type-2 fuzzy logic controller design using the GSO and FA algorithms. Int J Fuzzy Syst 23(1):42\u201357","journal-title":"Int J Fuzzy Syst"},{"issue":"1","key":"730_CR43","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1007\/s10479-017-2551-y","volume":"269","author":"SK Singh","year":"2018","unstructured":"Singh SK, Yadav SP (2018) Intuitionistic fuzzy multi-objective linear programming problem with various membership functions. Ann Oper Res 269(1):693\u2013707","journal-title":"Ann Oper Res"},{"issue":"6","key":"730_CR44","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 Evol Comput 11(6):712\u2013731","journal-title":"IEEE Trans Evol Comput"},{"issue":"2","key":"730_CR45","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1109\/TEVC.2017.2704118","volume":"22","author":"X Ma","year":"2017","unstructured":"Ma X, Zhang Q, Tian G, Yang J, Zhu Z (2017) On Tchebycheff decomposition approaches for multiobjective evolutionary optimization. IEEE Trans Evol Comput 22(2):226\u2013244","journal-title":"IEEE Trans Evol Comput"},{"issue":"1","key":"730_CR46","first-page":"53","volume":"12","author":"D Karaboa","year":"2004","unstructured":"Karaboa D, kdem S (2004) A simple and global optimization algorithm for engineering problems: differential evolution algorithm. Turk J Electr Eng Comput Sci 12(1):53\u201360","journal-title":"Turk J Electr Eng Comput Sci"},{"key":"730_CR47","volume-title":"EW 101: a first course in electronic warfare","author":"D Adamy","year":"2001","unstructured":"Adamy D (2001) EW 101: a first course in electronic warfare. Artech house, Chicago"},{"issue":"5","key":"730_CR48","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1109\/TEVC.2016.2519378","volume":"20","author":"R Cheng","year":"2016","unstructured":"Cheng R, Jin Y, Olhofer M et al (2016) A reference vector guided evolutionary algorithm for many-objective optimization. IEEE Trans Evol Comput 20(5):773\u2013791","journal-title":"IEEE Trans Evol Comput"},{"issue":"6","key":"730_CR49","doi-asserted-by":"publisher","first-page":"e0252293","DOI":"10.1371\/journal.pone.0252293","volume":"16","author":"L Zhao","year":"2021","unstructured":"Zhao L, Wang B, Shen C (2021) A multi-objective scheduling method for operational coordination time using improved triangular fuzzy number representation. PLoS One 16(6):e0252293","journal-title":"PLoS One"},{"issue":"4","key":"730_CR50","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1109\/MCI.2017.2742868","volume":"12","author":"Y Tian","year":"2017","unstructured":"Tian Y, Cheng R, Zhang X, Jin Y (2017) PlatEMO: a MATLAB platform for evolutionary multi-objective optimization [educational forum]. IEEE Comput Intell Mag 12(4):73\u201387","journal-title":"IEEE Comput Intell Mag"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-022-00730-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-022-00730-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-022-00730-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,30]],"date-time":"2022-10-30T06:36:07Z","timestamp":1667111767000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-022-00730-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,25]]},"references-count":50,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["730"],"URL":"https:\/\/doi.org\/10.1007\/s40747-022-00730-9","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"type":"print","value":"2199-4536"},{"type":"electronic","value":"2198-6053"}],"subject":[],"published":{"date-parts":[[2022,4,25]]},"assertion":[{"value":"4 October 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 March 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 April 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":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}