{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T13:33:03Z","timestamp":1760707983878},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2008,10,10]],"date-time":"2008-10-10T00:00:00Z","timestamp":1223596800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2009,6]]},"DOI":"10.1007\/s10115-008-0171-1","type":"journal-article","created":{"date-parts":[[2008,10,9]],"date-time":"2008-10-09T12:10:22Z","timestamp":1223554222000},"page":"283-309","source":"Crossref","is-referenced-by-count":40,"title":["Evolving rule induction algorithms with multi-objective grammar-based genetic programming"],"prefix":"10.1007","volume":"19","author":[{"given":"Gisele L.","family":"Pappa","sequence":"first","affiliation":[]},{"given":"Alex A.","family":"Freitas","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2008,10,10]]},"reference":[{"key":"171_CR1","volume-title":"Compilers: principles, techniques and tools","author":"AV Aho","year":"1986","unstructured":"Aho AV, Sethi R, Ullman JD (1986) Compilers: principles, techniques and tools, 1st edn. Addison-Wesley, Reading","edition":"1"},{"key":"171_CR2","volume-title":"GP\u2014an introduction. On the automatic evolution of computer programs and its applications","author":"W Banzhaf","year":"1998","unstructured":"Banzhaf W, Nordin P, Keller R, Francone F (1998) GP\u2014an introduction. On the automatic evolution of computer programs and its applications. Morgan Kaufmann, San Francisco"},{"key":"171_CR3","doi-asserted-by":"crossref","unstructured":"Bleuler S, Brack M, Thiele L, Zitzler E (2001) Multiobjective genetic programming: Reducing bloat using SPEA2. In: Proceedings of the 2001 congress on evolutionary computation\u2014CEC2001. IEEE, Korea, pp 536\u2013543","DOI":"10.1109\/CEC.2001.934438"},{"key":"171_CR4","first-page":"389","volume-title":"Proceedings of the 8th international workshop on machine learning","author":"CA Brunk","year":"1991","unstructured":"Brunk CA, Pazzani MJ (1991) An investigation of noise-tolerant relational concept learning algorithms. In: Birnbaum L, Collins G (eds) Proceedings of the 8th international workshop on machine learning. Morgan Kaufmann, San Francisco, pp 389\u2013393"},{"issue":"1","key":"171_CR5","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1093\/bioinformatics\/18.1.160","volume":"18","author":"A Clare","year":"2002","unstructured":"Clare A, King RD (2002) Machine learning of functional class from phenotype data. Bioinformatics 18(1): 160\u2013166","journal-title":"Bioinformatics"},{"key":"171_CR6","first-page":"151","volume-title":"EWSL-91: Proceedings of the working session on learning","author":"P Clark","year":"1991","unstructured":"Clark P, Boswell R (1991) Rule induction with cn2: some recent improvements. In: Kodratoff Y (eds) EWSL-91: Proceedings of the working session on learning. Springer, New York, pp 151\u2013163"},{"key":"171_CR7","unstructured":"Cleary R (2005) Extending grammar evolution with attribute grammars: an application to knapsack problems. Master\u2019s Thesis, University of Limerick"},{"issue":"3","key":"171_CR8","first-page":"129","volume":"1","author":"CAC Coello","year":"1999","unstructured":"Coello CAC (1999) A comprehensive survey of evolutionary-based multiobjective optimization techniques. Knowl Inf Syst 1(3): 129\u2013156","journal-title":"Knowl Inf Syst"},{"key":"171_CR9","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-5184-0","volume-title":"Algorithms for solving multi-objective problems","author":"CAC Coello","year":"2002","unstructured":"Coello CAC, Veldhuizen DV, Lamont G (2002) Algorithms for solving multi-objective problems. Kluwer, New York"},{"key":"171_CR10","unstructured":"Cohen WW (1993) Efficient pruning methods for separate-and-conquer rule learning systems. In: Proceedings of the 13th international joint conference on artificial intelligence (IJCAI-93), France, pp 988\u2013994"},{"key":"171_CR11","first-page":"115","volume-title":"Proceedings of the 12th international conference on machine learning","author":"WW Cohen","year":"1995","unstructured":"Cohen WW (1995) Fast effective rule induction. In: Prieditis A, Russell S (eds) Proceedings of the 12th international conference on machine learning. Morgan Kaufmann, Tahoe City, pp 115\u2013123"},{"key":"171_CR12","first-page":"11","volume-title":"Proceedings of the genetic and evolutionary computation conference, GECCO-2001","author":"ED De Jong","year":"2001","unstructured":"De Jong ED, Watson RA, Pollack JB (2001) Reducing bloat and promoting diversity using multi-objective methods. In: Spector L, Goodman E, Wu A, Langdon W, Voigt H-M, Gen M, Sen S, Dorigo M, Pezeshk S, Garzon M, Burke E (eds) Proceedings of the genetic and evolutionary computation conference, GECCO-2001. Morgan Kaufmann, San Francisco, pp 11\u201318"},{"key":"171_CR13","volume-title":"Multi-objective optimization using evolutionary algorithms","author":"K Deb","year":"2001","unstructured":"Deb K (2001) Multi-objective optimization using evolutionary algorithms. Wiley Interscience series in Systems and Optimization, Berlin"},{"key":"171_CR14","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1007\/3-540-45356-3_83","volume-title":"Parallel problem solving from nature\u2014PPSN VI","author":"K Deb","year":"2000","unstructured":"Deb K, Agrawal S, Pratap A, Meyarivan T (2000) A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In: Schoenauer M, Deb KGR, Yao X, Lutton E, Merelo JJ, Schwefel H (eds) Parallel problem solving from nature\u2014PPSN VI. Springer, Berlin, pp 849\u2013858"},{"issue":"2","key":"171_CR15","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1007\/s10115-003-0143-4","volume":"7","author":"ID Falco","year":"2005","unstructured":"Falco ID, Cioppa AD, Iazzetta A, Tarantino E (2005) An evolutionary approach for automatically extracting intelligible classification rules. Knowl Inf Syst 7(2): 179\u2013201","journal-title":"Knowl Inf Syst"},{"key":"171_CR16","doi-asserted-by":"crossref","unstructured":"Falco ID, Tarantino E, Cioppa AD, Fontanella F (2005) A novel grammar-based genetic programming approach to clustering. In: Proceedings of the 2005 ACM symposium on applied computing (SAC-05). ACM Press, New York, pp 928\u2013932","DOI":"10.1145\/1066677.1066891"},{"key":"171_CR17","doi-asserted-by":"crossref","unstructured":"Fayyad UM, Piatetsky-Shapiro G, Smyth P (1996) From data mining to knowledge discovery: an overview. In: Fayyad UM, Piatetsky-Shapiro G, Smyth P, Uthurusamy R (eds) Advances in knowledge discovery and data mining, AAAI\/MIT Press","DOI":"10.1145\/240455.240463"},{"key":"171_CR18","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-662-04923-5","volume-title":"Data mining and knowledge discovery with evolutionary algorithms","author":"AA Freitas","year":"2002","unstructured":"Freitas AA (2002) Data mining and knowledge discovery with evolutionary algorithms. Springer, Heidelberg"},{"issue":"2","key":"171_CR19","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1145\/1046456.1046467","volume":"6","author":"AA Freitas","year":"2004","unstructured":"Freitas AA (2004) A critical review of multi-objective optimization in data mining: a position paper. ACM SIGKDD Explor. Newsl. 6(2): 77\u201386","journal-title":"ACM SIGKDD Explor. Newsl."},{"issue":"1","key":"171_CR20","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1023\/A:1006524209794","volume":"13","author":"J Furnkranz","year":"1999","unstructured":"Furnkranz J (1999) Separate-and-conquer rule learning. Artif Intell Rev 13(1): 3\u201354","journal-title":"Artif Intell Rev"},{"key":"171_CR21","doi-asserted-by":"crossref","unstructured":"Furnkranz J, Widmer G (1994) Incremental reduced error pruning. In: Proceedings of the 11th international conference on machine learning, New Brunswick, NJ, pp 70\u201377","DOI":"10.1016\/B978-1-55860-335-6.50017-9"},{"key":"171_CR22","first-page":"377","volume-title":"Advances in genetic programming 2, chap 19","author":"F Gruau","year":"1996","unstructured":"Gruau F (1996) On using syntactic constraints with genetic programming. In: Angeline PJ, Kinnear KE Jr (eds) Advances in genetic programming 2, chap 19. MIT Press, Cambridge, pp 377\u2013394"},{"issue":"2","key":"171_CR23","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1109\/TCBB.2007.070203","volume":"4","author":"J Handl","year":"2007","unstructured":"Handl J, Kell DB, Knowles J (2007) Multiobjective optimization in bioinformatics and computational biology. IEEE\/ACM Trans Comput Biol Bioinf 4(2): 279\u2013292","journal-title":"IEEE\/ACM Trans Comput Biol Bioinf"},{"key":"171_CR24","first-page":"1081","volume-title":"Evolutionary multiobjective clustering, PPSN VIII: proceedings of the 8th international conference on parallel problem solving from nature","author":"J Handl","year":"2004","unstructured":"Handl J, Knowles J (2004) Evolutionary multiobjective clustering, PPSN VIII: proceedings of the 8th international conference on parallel problem solving from nature. Springer, London, pp 1081\u20131091"},{"issue":"2","key":"171_CR25","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1007\/s10994-005-5823-8","volume":"58","author":"ML Hetland","year":"2005","unstructured":"Hetland ML, Saetrom P (2005) Evolutionary rule mining in time series databases. Mach Learn 58(2): 107\u2013125","journal-title":"Mach Learn"},{"key":"171_CR26","doi-asserted-by":"crossref","unstructured":"Hoai NX, McKay RI, Abbass HA (2003) Tree adjoining grammars, language bias, and genetic programming. In: Ryan C, Soule T, Keijzer M, Tsang E, Poli R, Costa E (eds) Proceedings of the 6th European conference on genetic programming (EuroGP-03), vol 2610 of Lecure Notes in Computer Science. Springer, Essex, pp 335\u2013344","DOI":"10.1007\/3-540-36599-0_31"},{"key":"171_CR27","doi-asserted-by":"crossref","unstructured":"Hussain T, Browse R (1998) Network generating attribute grammar encoding. In: Proceedings of IEEE international joint conference on neural networks, pp 431\u2013436","DOI":"10.1109\/IJCNN.1998.682305"},{"key":"171_CR28","doi-asserted-by":"crossref","first-page":"1223","DOI":"10.1162\/0899766053630350","volume":"17","author":"H Jacobson","year":"2005","unstructured":"Jacobson H (2005) Rule extraction from recurrent neural networks: a taxonomy and review. Neural Comput. 17: 1223\u20131263","journal-title":"Neural Comput."},{"key":"171_CR29","doi-asserted-by":"crossref","unstructured":"Karwath A, King R (2002) Homology induction: the use of machine learning to improve sequence similarity searches. BMC Bioinf 3 (online publication)","DOI":"10.1186\/1471-2105-3-11"},{"key":"171_CR30","first-page":"116","volume-title":"Proceedings of the 1st annual conference on genetic programming (GP-96)","author":"RE Keller","year":"1996","unstructured":"Keller RE, Banzhaf W (1996) Genetic programming using genotype-phenotype mapping from linear genomes into linear phenotypes. In: Koza JR, Goldberg DE, Fogel DB, Riolo RL (eds) Proceedings of the 1st annual conference on genetic programming (GP-96). MIT Press, Stanford University, pp 116\u2013122"},{"key":"171_CR31","first-page":"424","volume":"2","author":"MH Law","year":"2004","unstructured":"Law MH, Topchy A, Jain A (2004) Multiobjective data clustering. Proc. IEEE Comput Soc Conf Comput Vis Pattern Recogn 2: 424\u2013430","journal-title":"Proc. IEEE Comput Soc Conf Comput Vis Pattern Recogn"},{"issue":"3","key":"171_CR32","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1023\/A:1007608224229","volume":"40","author":"T Lim","year":"2000","unstructured":"Lim T, Loh W, Shih Y (2000) A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms. Mach Learn 40(3): 203\u2013228","journal-title":"Mach Learn"},{"key":"171_CR33","doi-asserted-by":"crossref","unstructured":"McConaghy T, Gielen G (2006) Canonical form functions as a simple means for genetic programming to evolve human-interpretable functions. In: Proceedings of the 8th annual conference on genetic and evolutionary computation (GECCO-06). ACM Press, New York, pp 855\u2013862","DOI":"10.1145\/1143997.1144147"},{"key":"171_CR34","volume-title":"Machine learning, neural and statistical classification","year":"1994","unstructured":"Michie, D, Spiegelhalter, DJ, Taylor, CC, Campbell, J (eds) (1994) Machine learning, neural and statistical classification. Ellis Horwood, Upper Saddle River"},{"key":"171_CR35","first-page":"155","volume-title":"Genomics and Proteomics","author":"B Mirkin","year":"2000","unstructured":"Mirkin B, Ritter O (2000) A feature-based approach to discrimination and prediction of protein folding groups. Genomics and Proteomics. Springer, Heidelberg, pp 155\u2013177"},{"key":"171_CR36","unstructured":"Newman DJ, Hettich S, Blake C, Merz C (1998) UCI repository of machine learning databases"},{"key":"171_CR37","first-page":"343","volume-title":"Applications of evolutionary computing, vol 2037 of LNCS","author":"M O\u2019Neill","year":"2001","unstructured":"O\u2019Neill M, BrabazonA, Ryan C, Collins JJ (2001) Evolving market index trading rules using grammatical evolution. In: Boers EJW, Cagnoni S, Gottlieb J, Hart E, Lanzi PL, Raidl GR, Smith RE, Tijink H (eds) Applications of evolutionary computing, vol 2037 of LNCS. Springer, Heidelberg, pp 343\u2013352"},{"key":"171_CR38","volume-title":"Grammatical evolution evolutionary automatic programming in an arbitrary language","author":"M O\u2019Neill","year":"2003","unstructured":"O\u2019Neill M, Ryan C (2003) Grammatical evolution evolutionary automatic programming in an arbitrary language. Morgan Kaufmann, San Francisco"},{"issue":"1","key":"171_CR39","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1109\/TEVC.2006.880327","volume":"11","author":"A Ortega","year":"2007","unstructured":"Ortega A, de la Cruz M, Alfonseca M (2007) Christiansen grammar evolution: grammatical evolution with semantics. Evol Comput IEEE Trans 11(1): 77\u201390","journal-title":"Evol Comput IEEE Trans"},{"issue":"1","key":"171_CR40","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1023\/A:1022611825350","volume":"5","author":"G Pagallo","year":"1990","unstructured":"Pagallo G, Haussler D (1990) Boolean feature discovery in empirical learning. Mach Learn 5(1): 71\u201399","journal-title":"Mach Learn"},{"key":"171_CR41","doi-asserted-by":"crossref","unstructured":"Pappa GL (2007) Automatically evolving rule induction algorithms with grammar-based genetic programming. PhD Thesis, Computing Laboratory, University of Kent","DOI":"10.1007\/978-0-387-69935-6_6"},{"key":"171_CR42","first-page":"341","volume-title":"Proceedings of the 17th European conference on machine learning, vol 4212 of Lecture Notes in Computer Science","author":"GL Pappa","year":"2006","unstructured":"Pappa GL, Freitas AA (2006) Automatically evolving rule induction algorithms. In: Fuernkranz J, Scheffer T, Spiliopoulou M (eds) Proceedings of the 17th European conference on machine learning, vol 4212 of Lecture Notes in Computer Science. Springer, Berlin, pp 341\u2013352"},{"key":"171_CR43","first-page":"177","volume-title":"Soft computing for knowledge discovery and data mining","author":"GL Pappa","year":"2007","unstructured":"Pappa GL, Freitas AA (2007) Discovering new rule induction algorithms with grammar-based genetic programming. In: Maimon O, Rokach L (eds) Soft computing for knowledge discovery and data mining. Springer, Heidelberg, pp 177\u2013196"},{"key":"171_CR44","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1142\/9789812567796_0025","volume-title":"Applications of multi-objective evolutionary algorithms","author":"GL Pappa","year":"2004","unstructured":"Pappa GL, Freitas AA, Kaestner CAA (2004) Multi-objective algorithms for attribute selection in data mining. In: Coello CAC, Lamont G (eds) Applications of multi-objective evolutionary algorithms. World Scientific, Singapore, pp 603\u2013626"},{"issue":"2","key":"171_CR45","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/5254.850821","volume":"15","author":"MJ Pazzani","year":"2000","unstructured":"Pazzani MJ (2000) Knowledge discovery from data?. IEEE Intell Syst 15(2): 10\u201313","journal-title":"IEEE Intell Syst"},{"key":"171_CR46","doi-asserted-by":"crossref","unstructured":"Quinlan JR (1990) Induction of decision trees. In: Shavlik JW, Dietterich TG (eds) Readings in machine learning. Morgan Kaufmann (originally published in Machine Learning 1:81\u2013106, 1986)","DOI":"10.1007\/BF00116251"},{"key":"171_CR47","volume-title":"C4.5: programs for machine learning","author":"JR Quinlan","year":"1993","unstructured":"Quinlan JR (1993) C4.5: programs for machine learning. Morgan Kaufmann, San Francisco"},{"key":"171_CR48","first-page":"211","volume-title":"Proceedings of the 6th international conference on parallel problem solving from nature (PPSN)","author":"A Ratle","year":"2000","unstructured":"Ratle A, Sebag M (2000) Genetic programming and domain knowledge: beyond the limitations of grammar-guided machine discovery. In: Schoenauer M, Deb K, Rudolph G, Yao X, Lutton E, Merelo JJ, Schwefel H (eds) Proceedings of the 6th international conference on parallel problem solving from nature (PPSN). Springer, Heidelberg, pp 211\u2013220"},{"key":"171_CR49","first-page":"255","volume-title":"5th international conference on evolution artificielle, EA, vol 2310","author":"A Ratle","year":"2001","unstructured":"Ratle A, Sebag M (2001) Avoiding the bloat with probabilistic grammar-guided genetic programming. In: Collet P, Fonlupt C, Hao J-K, Lutton E, Schoenauer M (eds) 5th international conference on evolution artificielle, EA, vol 2310. Springer, Creusot, pp 255\u2013266"},{"issue":"2","key":"171_CR50","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1007\/s10115-004-0184-3","volume":"8","author":"K Rodrfguez-Vzquez","year":"2005","unstructured":"Rodrfguez-Vzquez K, Fleming PJ (2005) Evolution of mathematical models of chaotic systems based on multiobjective genetic programming. Knowl Inf Syst 8(2): 235\u2013256","journal-title":"Knowl Inf Syst"},{"issue":"5","key":"171_CR51","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s11257-004-7961-2","volume":"14","author":"C Romero","year":"2005","unstructured":"Romero C, Ventura S, De-Bra P (2005) Knowledge discovery with genetic programming for providing feedback to courseware authors. User Model User Adapt Interact 14(5): 425\u2013464","journal-title":"User Model User Adapt Interact"},{"key":"171_CR52","volume-title":"Learning with kernels: support vector machines, regularization, optimization, and beyond","author":"B Sch\u00f6lkopf","year":"2002","unstructured":"Sch\u00f6lkopf B, Smola AJ (2002) Learning with kernels: support vector machines, regularization, optimization, and beyond. The MIT Press, Cambridge"},{"issue":"4","key":"171_CR53","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1162\/evco.1998.6.4.293","volume":"6","author":"T Soule","year":"1998","unstructured":"Soule T, Foster JA (1998) Effects of code growth and parsimony pressure on populations in genetic programming. Evol Comput 6(4): 293\u2013309","journal-title":"Evol Comput"},{"issue":"suppl-2","key":"171_CR54","doi-asserted-by":"crossref","first-page":"W365","DOI":"10.1093\/nar\/gkh485","volume":"32","author":"D Szafron","year":"2004","unstructured":"Szafron D, Lu P, Greiner R, Wishart DS, Poulin B, Eisner R, Lu Z, Anvik J, Macdonell C, Fyshe A, Meeuwis D (2004) Proteome analyst: custom predictions with explanations in a web-based tool for high-throughput proteome annotations. Nucleic Acids Res 32(suppl-2): W365\u2013371","journal-title":"Nucleic Acids Res"},{"issue":"3","key":"171_CR55","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.artmed.2004.02.007","volume":"32","author":"A Tsakonas","year":"2004","unstructured":"Tsakonas A, Dounias G, Jantzen J, Axer H, Bjerregaard B, von Keyserlingk DG (2004) Evolving rule-based systems in two medical domains using genetic programming. Artif Intell Med 32(3): 195\u2013216","journal-title":"Artif Intell Med"},{"key":"171_CR56","unstructured":"Whigham PA (1995) Grammatically-based genetic programming. In: Rosca JP (ed) Proceedings of the workshop on GP: from theory to real-world applications, Tahoe City, pp 33\u201341"},{"key":"171_CR57","unstructured":"Whigham PA (1996) Grammatical bias for evolutionary learning. PhD Thesis, School of Computer Science, University College, University of New South Wales, Canberra, Australia"},{"key":"171_CR58","volume-title":"Data mining: practical machine learning tools and techniques with Java implementations","author":"IH Witten","year":"2005","unstructured":"Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques with Java implementations. Morgan Kaufmann, San Francisco"},{"issue":"1","key":"171_CR59","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/S0957-4174(98)00010-4","volume":"15","author":"ML Wong","year":"1998","unstructured":"Wong ML (1998) An adaptive knowledge-acquisition system using generic genetic programming. Exp Syst Appl 15(1): 47\u201358","journal-title":"Exp Syst Appl"},{"key":"171_CR60","volume-title":"Data mining using grammar-based genetic programming and applications","author":"ML Wong","year":"2000","unstructured":"Wong ML, Leung KS (2000) Data mining using grammar-based genetic programming and applications. Kluwer, Dordrecht"},{"key":"171_CR61","doi-asserted-by":"crossref","unstructured":"Zafra A, Ventura S (2007) Multi-objective genetic programming for multiple instance learning. In: Proceedings of European conference on machine learning\u2014ECML 2007, pp 790\u2013797","DOI":"10.1007\/978-3-540-74958-5_81"},{"key":"171_CR62","doi-asserted-by":"crossref","unstructured":"Zhang J (1992) Selecting typical instances in instance-based learning. In: Proceedings of the 9th international workshop on machine learning. Morgan Kaufmann, San Francisco, pp 470\u2013479","DOI":"10.1016\/B978-1-55860-247-2.50066-8"},{"issue":"3","key":"171_CR63","doi-asserted-by":"crossref","first-page":"809","DOI":"10.1016\/j.dss.2006.12.011","volume":"43","author":"H Zhao","year":"2007","unstructured":"Zhao H (2007) A multi-objective genetic programming approach to developing pareto optimal decision trees. Decis Support Syst 43(3): 809\u2013826","journal-title":"Decis Support Syst"},{"key":"171_CR64","unstructured":"Zitzler E, Laumanns M, Thiele L (2002) SPEA2: improving the strength pareto evolutionary algorithm for multiobjective optimization. In: Giannakoglou K, Tsahalis D, Periaux J, Papaliliou K, Fogarty T (eds) Evolutionary methods for design, optimisation and control with application to industrial problems. Proceedings of the EUROGEN2001 conference on international center for numerical methos in engineering (CIMNE), pp 95\u2013100"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-008-0171-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10115-008-0171-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-008-0171-1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,20]],"date-time":"2023-05-20T10:11:31Z","timestamp":1684577491000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10115-008-0171-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008,10,10]]},"references-count":64,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2009,6]]}},"alternative-id":["171"],"URL":"https:\/\/doi.org\/10.1007\/s10115-008-0171-1","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2008,10,10]]}}}