{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T22:22:43Z","timestamp":1783635763274,"version":"3.55.0"},"reference-count":64,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:00:00Z","timestamp":1781222400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000921","name":"European Cooperation in Science and Technology","doi-asserted-by":"publisher","award":["CA22137"],"award-info":[{"award-number":["CA22137"]}],"id":[{"id":"10.13039\/501100000921","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["P2-0209"],"award-info":[{"award-number":["P2-0209"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004329","name":"Slovenian Research and Innovation Agency","doi-asserted-by":"publisher","award":["GC-0001"],"award-info":[{"award-number":["GC-0001"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1016\/j.knosys.2026.116376","type":"journal-article","created":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T06:35:18Z","timestamp":1781246118000},"page":"116376","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Selecting test problems from benchmark suites in constrained multiobjective optimisation"],"prefix":"10.1016","volume":"348","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-6849-4088","authenticated-orcid":false,"given":"Jordan N.","family":"Cork","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6495-006X","authenticated-orcid":false,"given":"Tea","family":"Tu\u0161ar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4428-4255","authenticated-orcid":false,"given":"Bogdan","family":"Filipi\u010d","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.knosys.2026.116376_b1","series-title":"Benchmarking in optimization: Best practice and open issues","author":"Bartz-Beielstein","year":"2020"},{"key":"10.1016\/j.knosys.2026.116376_b2","series-title":"2017 IEEE Congress on Evolutionary Computation","first-page":"1127","article-title":"A note on constrained multi-objective optimization benchmark problems","author":"Tanabe","year":"2017"},{"key":"10.1016\/j.knosys.2026.116376_b3","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1016\/j.ins.2022.05.106","article-title":"Characterization of constrained continuous multiobjective optimization problems: A feature space perspective","volume":"607","author":"Vodopija","year":"2022","journal-title":"Inform. Sci."},{"issue":"1","key":"10.1016\/j.knosys.2026.116376_b4","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1109\/TEVC.2024.3366659","article-title":"Characterization of constrained continuous multiobjective optimization problems: A performance space perspective","volume":"29","author":"Vodopija","year":"2025","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"10.1016\/j.knosys.2026.116376_b5","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1109\/TEVC.2020.3020046","article-title":"Realistic constrained multiobjective optimization benchmark problems from design","volume":"25","author":"Picard","year":"2021","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b6","series-title":"Proceedings of the Genetic and Evolutionary Computation Conference","first-page":"576","article-title":"Analysis of real-world constrained multi-objective problems and performance comparison of multi-objective algorithms","author":"Nan","year":"2024"},{"key":"10.1016\/j.knosys.2026.116376_b7","series-title":"Evolutionary Multi-Criterion Optimization: 12th International Conference (EMO 2023)","first-page":"333","article-title":"Performance evaluation of multi-objective evolutionary algorithms using artificial and real-world problems","author":"Ishibuchi","year":"2023"},{"issue":"2","key":"10.1016\/j.knosys.2026.116376_b8","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1109\/TEVC.2016.2587749","article-title":"Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes","volume":"21","author":"Ishibuchi","year":"2017","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"10.1016\/j.knosys.2026.116376_b9","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1109\/MCI.2021.3129961","article-title":"Difficulties in fair performance comparison of multi-objective evolutionary algorithms","volume":"17","author":"Ishibuchi","year":"2022","journal-title":"IEEE Comput. Intell. Mag."},{"issue":"6","key":"10.1016\/j.knosys.2026.116376_b10","doi-asserted-by":"crossref","first-page":"972","DOI":"10.1109\/TEVC.2019.2896967","article-title":"Evolutionary constrained multiobjective optimization: Test suite construction and performance comparisons","volume":"23","author":"Ma","year":"2019","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b11","series-title":"Proceedings of the Genetic and Evolutionary Computation Conference","first-page":"829","article-title":"Exploratory landscape analysis","author":"Mersmann","year":"2011"},{"issue":"5","key":"10.1016\/j.knosys.2026.116376_b12","doi-asserted-by":"crossref","first-page":"1427","DOI":"10.1109\/TEVC.2022.3208595","article-title":"An instance space analysis of constrained multiobjective optimization problems","volume":"27","author":"Alsouly","year":"2023","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b13","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2024.101716","article-title":"On the representativeness metric of benchmark problems in numerical optimization","volume":"91","author":"Chen","year":"2024","journal-title":"Swarm Evol. Comput."},{"issue":"6","key":"10.1016\/j.knosys.2026.116376_b14","doi-asserted-by":"crossref","first-page":"1293","DOI":"10.1109\/TEVC.2022.3210897","article-title":"Anytime performance assessment in blackbox optimization benchmarking","volume":"26","author":"Hansen","year":"2022","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"10.1016\/j.knosys.2026.116376_b15","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1109\/TEVC.2018.2855411","article-title":"Two-archive evolutionary algorithm for constrained multiobjective optimization","volume":"23","author":"Li","year":"2019","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b16","series-title":"Multiobjective Optimization Test Instances for the CEC 2009 Special Session and Competition","author":"Zhang","year":"2008"},{"issue":"3","key":"10.1016\/j.knosys.2026.116376_b17","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1162\/evco.1994.2.3.221","article-title":"Multiobjective optimization using nondominated sorting in genetic algorithms","volume":"2","author":"Srinivas","year":"1994","journal-title":"Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b18","series-title":"1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century","first-page":"1556","article-title":"GA-based decision support system for multicriteria optimization","volume":"Vol. 2","author":"Tanaka","year":"1995"},{"key":"10.1016\/j.knosys.2026.116376_b19","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1007\/BF01743536","article-title":"A new method to solve generalized multicriteria optimization problems using the simple genetic algorithm","volume":"10","author":"Osyczka","year":"1995","journal-title":"Struct. Optim."},{"key":"10.1016\/j.knosys.2026.116376_b20","unstructured":"T.T. Binh, U. Korn, Mobes: A Multiobjective Evolution Strategy for Constrained Optimization Problems, in: Proceedings of the 3rd International Mendel Conference on Genetic Algorithms, MENDEL \u201997, 1997, pp. 176\u2013182."},{"key":"10.1016\/j.knosys.2026.116376_b21","series-title":"Proceedings of Evolutionary Algorithms in Engineering and Computer Science, EUROGEN-99","first-page":"135","article-title":"Evolutionary algorithms for multi-criterion optimization in engineering design","author":"Deb","year":"1999"},{"issue":"2","key":"10.1016\/j.knosys.2026.116376_b22","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1162\/106365600568202","article-title":"Comparison of multiobjective evolutionary algorithms: Empirical results","volume":"8","author":"Zitzler","year":"2000","journal-title":"Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b23","series-title":"Proceedings of the 2002 Congress on Evolutionary Computation","first-page":"825","article-title":"Scalable multi-objective optimization test problems","volume":"Vol. 1","author":"Deb","year":"2002"},{"key":"10.1016\/j.knosys.2026.116376_b24","series-title":"Proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization","first-page":"280","article-title":"A scalable multi-objective test problem toolkit","author":"Huband","year":"2005"},{"key":"10.1016\/j.knosys.2026.116376_b25","series-title":"Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization","first-page":"284","article-title":"Constrained test problems for multi-objective evolutionary optimization","author":"Deb","year":"2001"},{"issue":"4","key":"10.1016\/j.knosys.2026.116376_b26","doi-asserted-by":"crossref","first-page":"602","DOI":"10.1109\/TEVC.2013.2281534","article-title":"An evolutionary many-objective optimization algorithm using reference-point based nondominated sorting approach, part II: Handling constraints and extending to an adaptive approach","volume":"18","author":"Jain","year":"2014","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b27","series-title":"2016 IEEE Congress on Evolutionary Computation","first-page":"4175","article-title":"A comparative study of constraint-handling techniques in evolutionary constrained multiobjective optimization","author":"Li","year":"2016"},{"issue":"5","key":"10.1016\/j.knosys.2026.116376_b28","doi-asserted-by":"crossref","first-page":"870","DOI":"10.1109\/TEVC.2019.2894743","article-title":"Handling constrained multiobjective optimization problems with constraints in both the decision and objective spaces","volume":"23","author":"Liu","year":"2019","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b29","doi-asserted-by":"crossref","first-page":"12491","DOI":"10.1007\/s00500-019-03794-x","article-title":"An improved epsilon constraint-handling method in MOEA\/D for CMOPs with Large Infeasible Regions","volume":"23","author":"Fan","year":"2019","journal-title":"Soft Comput."},{"issue":"3","key":"10.1016\/j.knosys.2026.116376_b30","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1162\/evco_a_00259","article-title":"Difficulty adjustable and scalable constrained multiobjective test problem toolkit","volume":"28","author":"Fan","year":"2020","journal-title":"Evol. Comput."},{"issue":"1","key":"10.1016\/j.knosys.2026.116376_b31","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1109\/TEVC.2020.3011829","article-title":"Constrained multiobjective optimization: Test problem construction and performance evaluations","volume":"25","author":"Zhou","year":"2021","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b32","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2022.101209","article-title":"Constrained multimodal multi-objective optimization: Test problem construction and algorithm design","volume":"76","author":"Ming","year":"2023","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b33","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2024.101504","article-title":"Benchmark problems for large-scale constrained multi-objective optimization with baseline results","volume":"86","author":"Qiao","year":"2024","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b34","series-title":"2019 IEEE Congress on Evolutionary Computation","first-page":"2034","article-title":"Regular Pareto front shape is not realistic","author":"Ishibuchi","year":"2019"},{"key":"10.1016\/j.knosys.2026.116376_b35","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2021.100961","article-title":"A benchmark-suite of real-world constrained multi-objective optimization problems and some baseline results","volume":"67","author":"Kumar","year":"2021","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b36","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2020.106078","article-title":"An easy-to-use real-world multi-objective optimization problem suite","volume":"89","author":"Tanabe","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.knosys.2026.116376_b37","series-title":"Applications of Evolutionary Computation","first-page":"442","article-title":"Towards constructing a suite of multi-objective optimization problems with diverse landscapes","author":"Andova","year":"2023"},{"key":"10.1016\/j.knosys.2026.116376_b38","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1080\/10556788.2020.1808977","article-title":"COCO: A platform for comparing continuous optimizers in a black-box setting","volume":"36","author":"Hansen","year":"2021","journal-title":"Optim. Methods Softw."},{"key":"10.1016\/j.knosys.2026.116376_b39","series-title":"Proceedings of the Genetic and Evolutionary Computation Conference","first-page":"620","article-title":"SELECTOR: Selecting a representative benchmark suite for reproducible statistical comparison","author":"Cenikj","year":"2022"},{"key":"10.1016\/j.knosys.2026.116376_b40","doi-asserted-by":"crossref","DOI":"10.1016\/j.swevo.2023.101378","article-title":"Choice of benchmark optimization problems does matter","volume":"83","author":"Piotrowski","year":"2023","journal-title":"Swarm Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b41","doi-asserted-by":"crossref","first-page":"89497","DOI":"10.1109\/ACCESS.2020.2990567","article-title":"Pymoo: Multi-objective optimization in python","volume":"8","author":"Blank","year":"2020","journal-title":"IEEE Access"},{"issue":"2","key":"10.1016\/j.knosys.2026.116376_b42","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","article-title":"A fast and elitist multiobjective genetic algorithm: NSGA-II","volume":"6","author":"Deb","year":"2002","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"4","key":"10.1016\/j.knosys.2026.116376_b43","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1109\/TEVC.2013.2281535","article-title":"An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: Solving problems with box constraints","volume":"18","author":"Deb","year":"2014","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b44","unstructured":"R. Angira, B. Babu, Non-dominated sorting differential evolution (NSDE): An extension of differential evolution for multi-objective optimization, in: Proceedings of the 2nd Indian International Conference on Artificial Intelligence, IICAI-05, Pune, India, 2005, pp. 1428\u20131443."},{"key":"10.1016\/j.knosys.2026.116376_b45","unstructured":"J. MacQueen, Some methods for classification and analysis of multivariate observations, in: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Vol. 1, 1967, pp. 281\u2013297."},{"issue":"85","key":"10.1016\/j.knosys.2026.116376_b46","first-page":"2825","article-title":"Scikit-learn: Machine learning in python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"issue":"1","key":"10.1016\/j.knosys.2026.116376_b47","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1109\/TEVC.2020.2992387","article-title":"Generating well-spaced points on a unit simplex for evolutionary many-objective optimization","volume":"25","author":"Blank","year":"2021","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b48","series-title":"SPEA2: Improving the Strength Pareto Evolutionary Algorithm","author":"Zitzler","year":"2001"},{"key":"10.1016\/j.knosys.2026.116376_b49","series-title":"Proceedings of the Genetic and Evolutionary Computation Conference, GECCO \u201919","first-page":"595","article-title":"An adaptive evolutionary algorithm based on non-euclidean geometry for many-objective optimization","author":"Panichella","year":"2019"},{"issue":"6","key":"10.1016\/j.knosys.2026.116376_b50","doi-asserted-by":"crossref","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","article-title":"MOEA\/D: A multiobjective evolutionary algorithm based on decomposition","volume":"11","author":"Zhang","year":"2007","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b51","series-title":"2005 IEEE Congress on Evolutionary Computation","first-page":"443","article-title":"GDE3: The third evolution step of generalized differential evolution","volume":"Vol. 1","author":"Kukkonen","year":"2005"},{"key":"10.1016\/j.knosys.2026.116376_b52","doi-asserted-by":"crossref","first-page":"1455","DOI":"10.1007\/s00158-019-02272-0","article-title":"Many-objective differential evolution optimization based on reference points: NSDE-R","volume":"60","author":"Reddy","year":"2019","journal-title":"Struct. Multidiscip. Optim."},{"issue":"10","key":"10.1016\/j.knosys.2026.116376_b53","doi-asserted-by":"crossref","first-page":"10163","DOI":"10.1109\/TCYB.2021.3056176","article-title":"Handling constrained multiobjective optimization problems via bidirectional coevolution","volume":"52","author":"Liu","year":"2022","journal-title":"IEEE Trans. Cybern."},{"issue":"1","key":"10.1016\/j.knosys.2026.116376_b54","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1109\/TEVC.2020.3004012","article-title":"A coevolutionary framework for constrained multiobjective optimization problems","volume":"25","author":"Tian","year":"2021","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"10.1016\/j.knosys.2026.116376_b55","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1109\/TEVC.2023.3260306","article-title":"A multipopulation evolutionary algorithm using new cooperative mechanism for solving multiobjective problems with multiconstraint","volume":"28","author":"Zou","year":"2024","journal-title":"IEEE Trans. Evol. Comput."},{"key":"10.1016\/j.knosys.2026.116376_b56","doi-asserted-by":"crossref","DOI":"10.1016\/j.ces.2022.118196","article-title":"Multi-objective optimization of adiabatic styrene reactors using generalized differential evolution 3 (GDE3)","volume":"265","author":"Leite","year":"2023","journal-title":"Chem. Eng. Sci."},{"key":"10.1016\/j.knosys.2026.116376_b57","series-title":"Pymoode: Differential evolution-based multi-objective optimization in python","author":"Leite","year":"2023"},{"issue":"4","key":"10.1016\/j.knosys.2026.116376_b58","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1109\/MCI.2017.2742868","article-title":"PlatEMO: A MATLAB platform for evolutionary multi-objective optimization","volume":"12","author":"Tian","year":"2017","journal-title":"IEEE Comput. Intell. Mag."},{"key":"10.1016\/j.knosys.2026.116376_b59","series-title":"Proceedings of IEEE International Conference on Evolutionary Computation","first-page":"312","article-title":"Adapting arbitrary normal mutation distributions in evolution strategies: The covariance matrix adaptation","author":"Hansen","year":"1996"},{"key":"10.1016\/j.knosys.2026.116376_b60","series-title":"Advances in Optimization and Numerical Analysis","first-page":"51","article-title":"A direct search optimization method that models the objective and constraint functions by linear interpolation","volume":"vol. 275","author":"Powell","year":"1994"},{"key":"10.1016\/j.knosys.2026.116376_b61","series-title":"A Software Package for Sequential Quadratic Programming","author":"Kraft","year":"1988"},{"key":"10.1016\/j.knosys.2026.116376_b62","series-title":"Pycma","author":"Hansen","year":"2019"},{"key":"10.1016\/j.knosys.2026.116376_b63","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1038\/s41592-019-0686-2","article-title":"SciPy 1.0: Fundamental algorithms for scientific computing in python","volume":"17","author":"Virtanen","year":"2020","journal-title":"Nature Methods"},{"issue":"11","key":"10.1016\/j.knosys.2026.116376_b64","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126011020?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126011020?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T22:08:20Z","timestamp":1783634900000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705126011020"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":64,"alternative-id":["S0950705126011020"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2026.116376","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2026,8]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Selecting test problems from benchmark suites in constrained multiobjective optimisation","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2026.116376","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"116376"}}