Welcome to EMOFRBSs

The Evolutionary Multiobjective Optimization of
Fuzzy Rule-Based Systems
Bibliography Page

Abstract

Since pioneering works by Prof. Hisao Ishibuchi in middle nineties, Pareto-based Evolutionary Multiobjective Optimization (EMO) of Fuzzy Rule-Based Systems (FRBSs) is nowadays a well-established research area. It is a branch of the more general Evolutionary/Genetic Fuzzy Systems (see F. Herrera, "Genetic Fuzzy systems: Taxonomy, current research trends and prospects", Evo. Intel. (2008), 1:27-46 and this bibliography page on recent publications on the topic, maintained by R. Alcalá and M. J. Gacto). In Pareto-based evolutionary optimization the set of objetives used are not aggregated in order to reconduct the problem to a single objective optimization problem. This page is intended to collect as many references as possible to papers dealing with Pareto-based EMO of FRBSs. (Pareto-based) EMOs of FRBSs are special cases of Multiobjective Evolutionary Fuzzy Systems (MEFSs), which include the class of Multiobjective Genetic Fuzzy Systems (MGFSs). For a review on the last topic, see H. Ishibuchi, "Multiobjective Genetic Fuzzy Systems: review and future research directions", in Proc. of Fuzz-IEEE'07, pp. 1-6). For a more general overview of multiobjective optimization in machine learning please refer to Y. Jin and B. Sendhoff, "Pareto-Based Multiobjective Machine Learning: An Overview and Case Studies", IEEE Trans. on Syst., Man and Cyb., part C, (2008), 38(3):397- 415. For a more general bibliography on EMO, please refer to the EMOO bibliography page, mantained by Prof. Carlos A. Coello Coello.



This page was created and is mantained by Marco Cococcioni

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AuthorTitleYearJournal/ProceedingsReftypeDOI/URL
Abbod MF, Mahfouf M, Linkens DA Multi-objective genetic optimisation for self-organising fuzzy logic control 1998 in: Proc. of the 1998 UKACC International Conference on Control (UKACC'98)   inproceedings DOI  
Alcala R, Alcala-Fdez J, Gacto MJ, Herrera F On the Usefulness of MOEAs for Getting Compact FRBSs Under Parameter Tuning and Rule Selection 2008 Multi-objective Evolutionary Algorithms for Knowledge Discovery from Data Bases   inbook  
Alcala R, Alcala-Fdez J, Gacto MJ, Herrera F On the use of Multiobjective Genetic Algorithms to Improve the Accuracy-Interpretability Trade-Off of Fuzzy Rule-Based Systems 2008 in: Multi-objective Evolutionary Algorithms for Knowledge Discovery from Data Bases, Ghosh A, Dehuri S, Ghosh S (eds), Springer, 2008Multi-objective Evolutionary Algorithms for Knowledge Discovery from Data Bases   inbook  
Alcala R, Alcala-Fdez J, Gacto MJ, Herrera F A Multi-objective Genetic Algorithm for Tuning and Rule Selection to Obtain Accurate and Compact Linguistic Fuzzy Rule-Based Systems 2007 International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems   article  
Alcala R, Alcala-Fdez J, Gacto MJ, Herrera F A Multi-Objective Evolutionary Algorithm for Rule Selection and Tuning on Fuzzy Rule-Based Systems 2007 in: Proc. of the 16th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'07)   inproceedings  
Alcala R, Alcala-Fdez J, Gacto MJ, Herrera F Obtencion de Sistemas Basados en Reglas Difusas Precisos y Compactos Mediante Algoritmos Geneticos Multiobjetivo 2006 XIII Congreso Espanol sobre Tecnologias y Logica Fuzzy (ESTYLF06)   inproceedings  
Alcala R, Alcala-Fdez J, Gacto MJ, Herrera F Obtaining Compact and Still Accurate Linguistic Fuzzy Rule-Based Systems by Using Multi-Objetive Genetic Algorithms 2006 in: Symposium on Fuzzy Systems in Computer Science (FSCS'06)   inproceedings  
Alcala R, Benitez JM, Casillas J, Castro JL, Cordon O, Gonzalez A, Herrera F, Perez R Multicriteria genetic tuning for the optimization and control of HVAC systems 2003 Applied Decision Support with Soft Computing   inbook  
Alcala R, Casillas J, Castro JL, Gonzalez A, Herrera F A Multicriteria Genetic Tuning for Fuzzy Logic Controllers 2001 Mathware and Soft Computing   article  
Alcala R, Ducange P, Herrera F, Lazzerini B, Marcelloni F A Multi-objective Evolutionary Approach to Concurrently Learn Rule and Data Bases of Linguistic Fuzzy Rule-Based Systems 2009 IEEE Transactions on Fuzzy Systems   article DOI  
Alcala R, Gacto MJ, Herrera F A Fast and Scalable Multi-Objective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems 2011 IEEE Transactions on Fuzzy Systems   article DOI  
Alcala R, Nojima Y, Herrera F, Ishibuchi H Multiobjective Genetic Fuzzy Rule Selection of Single Granularity-Based Fuzzy Classification Rules and its Interaction with the Lateral Tuning of Membership Functions 2011 Soft Computing   article DOI  
Alcala R, Nojima Y, Herrera F, Ishibuchi H Generating Single Granularity Based Fuzzy Classification Rules for Multiobjective Genetic Fuzzy Rule Selection 2009 in: Proc. of the 18th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'09)   inproceedings DOI  
Alonso JM, Magdalena L, Cordon O Embedding HILK in a three-objective evolutionary algorithm with the aim of modeling highly interpretable fuzzy rule-based classifiers 2010 in Proc. of the 4th Int. Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS'10)   inproceedings DOI  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F Learning concurrently data and rule bases of Mamdani fuzzy rule-based systems by exploiting a novel interpretability index 2011 Soft Computing   article DOI  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F Learning Knowledge Bases of Multi-objective Evolutionary Fuzzy Systems by Simultaneously Optimizing Accuracy, Complexity and Partition Integrity 2011 Soft Computing   article DOI  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F Exploiting a Three-Objective Evolutionary Algorithm for Generating Mamdani Fuzzy Rule-Based Systems 2010 in Proc. of the 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'10)   inproceedings  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F Learning Concurrently Partition Granularities and Rule Bases of Mamdani Fuzzy Systems in a Multi-objective Evolutionary Framework 2009 International Journal of Approximate Reasoning   article DOI  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F Multi-objective Evolutionary Learning of Granularity, Membership Function Parameters and Rules of Mamdani Fuzzy Systems 2009 Evolutionary Ingelligence   article DOI  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F Learning Concurrently Granularity, Membership Function Parameters and Rules of Mamdani Fuzzy Rule-based Systems 2009 in Proc. of the joint International Fuzzy Systems Association World Congress and the European Society for Fuzzy Logic and Technology Conference (IFSA/EUSFLAT 2009)   inproceedings  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F A Three-Objective Evolutionary Approach to Generate Mamdani Fuzzy Rule-Based Systems 2009 in Proc. of the 4th International Conference of Hybrid Artificial Intelligent Systems (HIS2009   inproceedings  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F Learning Concurrently Granularity, Membership Function Parameters and Rules of Mamdani Fuzzy Rule-based Systems 2009 in Proc. of the IFSA'09/EUSFLAT'09 International Conference   inproceedings  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F Exploiting a New Interpretability Index in the Multi-Objective Evolutionary Learning of Mamdani Fuzzy Rule-based Systems 2009 in Proc. of the 9th Int. Conf. on Intelligent Systems Design and Applications (ISDA'09)   inproceedings  
Antonelli M, Ducange P, Lazzerini B, Marcelloni F A Multi-objective Genetic Approach to Concurrently Learn Partition Granularity and Rule Bases of Mamdani Fuzzy Systems 2008 in Proc. of 8th International Conference on Hybrid Intelligent Systems (HIS'08)   inproceedings  
Antonelli M, Ducange P, Lazzerini M, Marcelloni F Multi-objective Evolutionary Generation of Mamdani Fuzzy Rule-Based Systems based on Rule and Condition Selection 2011 in Proc. of the 5th IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS'11)   inproceedings  
Antonelli M, Ducange P, Marcelloni F An experimental study on evolutionary fuzzy classifiers designed for managing imbalanced datasets 2014 Neurocomputing   article DOI  
Antonelli M, Ducange P, Marcelloni F A fast and efficient multi-objective evolutionary learning scheme for fuzzy rule-based classifiers 2014 Information Sciences   article DOI  
Antonelli M, Ducange P, Marcelloni F An efficient multi-objective evolutionary fuzzy system for regression problems 2013 International Journal of Approximate Reasoning   article DOI  
Antonelli M, Ducange P, Marcelloni F Genetic Training Instance Selection in Multi-Objective Evolutionary Fuzzy Systems: A Co-evolutionary Approach 2012 IEEE Transactions on Fuzzy Systems   article DOI  
Antonelli M, Ducange P, Marcelloni F A New Approach to Handle High Dimensional and Large Datasets in Multi-objective Evolutionary Fuzzy Systems 2011 in Proc. of the 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'11)   inproceedings  
Antonelli M, Ducange P, Marcelloni F Exploiting a Coevolutionary Approach to Concurrently Select Training Instances and Learn Rule Bases of Mamdani Fuzzy Systems 2010 in Proc. of the 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'10)   inproceedings  
Antonelli M, Ducange P, Marcelloni F, Segatori A On the Influence of Feature Selection in Fuzzy Rule-based Regression Model Generation 2015 Information Sciences   article DOI  
Antonelli M, Ducange P, Marcelloni F, Segatori A Evolutionary fuzzy classifiers for imbalanced datasets: An experimental comparison 2013 IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013 Joint   inproceedings DOI  
Ascia G, Catania V, Di Nuovo AG, Palesi M, Patti D Performance Evaluation of Efficient Multi-Objective Evolutionary Algorithms for Design Space Exploration of Embedded Computer Systems 2011 Applied Soft Computing   article DOI  
Berlanga FJ, del Jesus MJ, Gonzalez P, Herrera F Multiobjective evolutionary induction of subgroup discovery rules in a market problem 2005 in: Proc. of the 2005 International Conference on Machine Intelligence   inproceedings  
Berlanga FJ, del Jesus MJ, Gonzalez P, Herrera F, Mesonero M Multiobjective Evolutionary Induction of Subgroup Discovery Fuzzy Rules: A Case Study in Marketing 2006 in: Proc. of the 6th Industrial Conference on Data Mining (ICDM'06)   inproceedings  
Bica B, Chipperfield AJ, Fleming PJ, MacKenzie S Enhancing the Performance of a Multivariable Fuzzy Controller by Means of a Multiobjective Genetic Programming and Statistical Analysis 2000 in: Proc. of the 26th Annual Conference of the IEEE Industrial Electronics Society (IECON'00)   inproceedings  
Blumel AL, Hughes EJ, White BA Multi-objective Evolutionary Design of Fuzzy Autopilot Controller 2001 in: Proc. of the 1st International Conference on Evolutionary Multi-Criterion Optimization (EMO'01)   inproceedings  
Blumel AL, Hughes EJ, White BA Fuzzy autopilot design using a multiobjective evolutionary algorithm 2000 in: Proc. of the 2000 Congress on Evolutionary Computation (CEC'00)   inproceedings  
Blumel AL, White BA Multiobjective optimization of fuzzy logic scheduled controllers for missile autopilot design 2001 in: Proc. of the 9th IFSA World Congress and 20th NAFIPS International Conference (IFSA-NAFIPS'01)   inproceedings  
Botta A, Ducange P, Lazzerini B, Marcelloni F A multi-objective cooperative coevolutionary approach to Mamdani fuzzy system generation 2008 in Proc. of 12th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU'08)   inproceedings  
Botta A, Lazzerini B, Marcelloni F, Stefanescu D Context adaptation of fuzzy systems through a multi-objective evolutionary approach based on a novel interpretability index 2008 Soft Computing   article DOI  
Cannone R, Alonso JM, Magdalena L Multi-objective design of highly interpretable fuzzy rule-based classi?ers with semantic cointension 2011 in Proc. of the 5th Int. Workshop on Genet. Evol. Fuzzy Syst. (GEFS'11)"   inproceedings DOI  
Cannone R, Alonso JM, Magdalena L An Empirical Study on Interpretability Indexes through Multi-objective Evolutionary Algorithms 2011 in Proc. of the 9th International Workshop on Fuzzy Logic and Applications (WILF'11)   inproceedings DOI  
Cardenas EH, Carmago HA Multiobjective Genetic Optimization of Fuzzy Partitions and T-Norm Parameters in Fuzzy Classifiers 2012 in Proc. of the 2012 Brazilian Symposium on Neural Networks (SBRN'12)   inproceedings DOI  
Carmona CJ, Gonzalez P, del Jesus MJ, Herrera F NMEEF-SD: Non-dominated Multiobjective Evolutionary Algorithm for Extracting Fuzzy Rules in Subgroup Discovery 2010 IEEE Transactions on Fuzzy Systems   article DOI  
Casillas J, Delgado O, Martinez-Lopez FJ Predictive knowledge discovery by multiobjective genetic fuzzy systems for estimating consumer behavior models 2005 in: Proc. of the 4th International Conference in Fuzzy Logic and Technology (EUSFLAT'05)   inproceedings  
Casillas J, Delgado O, Martinez-Lopez FJ Una Metodologia de KDD basada en Sistemas Difusos Geneticos Multiobjetivo para Modelado Causal en Marketing 2005 in Proc. of the 4th Congreso Espanol sobre Metahuristicas, Algoritmos Evolutivos y Bioinspirados (MAEB'05)   inproceedings  
Casillas J, Martinez-Lopez FJ Consumer modeling by multiobjective genetic fuzzy systems: a descriptive rule induction approach 2007 in: Proc. of the 36th European Marketing Academy Conference (EMAC'07)   inproceedings  
Casillas J, Martinez-Lopez FJ Modeling vague data with genetic fuzzy systems under a combination of crisp and imprecise criteria 2007 in Proc. of the first IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM 2007)   inproceedings  
Casillas J, Martinez P, Benitez AD Learning consistent, complete and compact sets of fuzzy rules in conjunctive normal form for regression problems 2009 Soft Computing   article DOI  
Castillo O, Melin P, Alanis A, Montiel O, Sepulveda R Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms 2011 Soft Computing   article DOI  
Castillo O, Melin P, Alanis A, Montiel O, Sepulveda R Optimization of interval type-2 fuzzy logic controllers using evolutionary algorithms 2011 Soft Computing   article DOI  
Chen J, Mahfouf M Interpretable fuzzy modeling using multi-objective immune-inspired optimization algorithms 2010 in Proc. of the 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'10)   inproceedings DOI  
Chen J, Mahfouf M An Artificial Immune Systems based Predictive Modelling Approach for the multi-objective elicitation of mamdani fuzzy rules: A special application to modelling Alloys 2009 in Proc. of the 2009 IEEE Int. Conf. on Systems, Man, and Cybernetics (IEEE-SMC'09)   inproceedings DOI  
Chen J, Mahfouf M An immune algorithm based fuzzy predictive modeling mechanism using variable length coding and multi-objective optimization allied to engineering materials processing 2008 in Proc. of the 2008 IEEE Int. Conf. on Granular Computing (IEEE-GrC'08)   inproceedings DOI  
Chipperfield AJ, Bica B, Fleming PJ Fuzzy scheduling control of a gas turbine aero-engine: a multiobjective approach 2002 IEEE Transactions on Industrial Electronics   article  
Cococcioni M, Corsini G, Lazzerini B, Marcelloni F Solving the Ocean Color Inverse Problem by Using Evolutionary Multi-Objective Optimization of Neuro-Fuzzy Systems 2008 KES Journal   article  
Cococcioni M, Ducange P, Lazzerini B, Marcelloni F A comparison of multi-objective evolutionary algorithms in fuzzy Rule-Based systems generation 2006 in Proc. of the 2006 North American Fuzzy Information Processing Society (NAFIPS'06)   inproceedings  
Cococcioni M, Ducange P, Lazzerini B, Marcelloni F A Pareto-based Multi-Objective Evolutionary Approach to the Identification of Mamdani Fuzzy Systems 2007 Soft Computing   article  
Cococcioni M, Ducange P, Lazzerini B, Marcelloni F A New Multi-Objective Evolutionary Algorithm based on Convex Hull for Binary Classifier Optimization 2007 in Proc. of the 2007 IEEE Congress on Evolutionary Computation (CEC'07)   inproceedings  
Cococcioni M, Ducange P, Lazzerini B, Marcelloni F Evolutionary Multiobjective Optimization of Fuzzy Rule-Based Classifiers in the ROC space 2007 in Proc. of the 16th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'07)   inproceedings  
Cococcioni M, Ducange P, Lazzerini B, Marcelloni F, Vecchio, M. Identification of Mamdani Fuzzy Systems based on a Multi-Objective Genetic Algorithm 2005 First Italian Workshop on Evolutionary Computation (GSICE'05)   inproceedings  
Cococcioni M, Grasso R, Rixen M A Hybrid Continuity Preserving Inference Strategy to Speed Up Takagi-Sugeno Multiobjective Genetic Fuzzy Systems 2011 in Proc. of 5th IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS'11)   inproceedings  
Cococcioni M, Guasqui P, Lazzerini B, Marcelloni F Identification of Takagi-Sugeno Fuzzy Systems based on Multi-Objective Genetic Algorithms 2005 in Proc. of the 6th International Workshop on Fuzzy Logic and Applications (WILF'05)   inproceedings  
Cococcioni M, Lazzerini B Multiobjective evolutionary optimization of quadratic Takagi-Sugeno fuzzy rules for remote bathymetry estimation 2015 IEEE/MTS OCEANS 2015-Genova   inproceedings DOI  
Cococcioni M, Lazzerini B, Marcelloni F Towards Efficient Multi-objective Genetic Takagi-Sugeno Fuzzy Systems for High Dimensional Problems 2010 Computational Intelligence in Expensive Optimization Problems   inbook DOI  
Cococcioni M, Lazzerini B, Marcelloni F Fast Multiobjective Genetic Rule Learning Using an Efficient Method for Takagi-Sugeno Fuzzy Systems Identification 2008 in Proc. of 8th Int. Conf. on Hybrid Intelligent Systems (HIS'08)   inproceedings  
Cococcioni M, Lazzerini B, Marcelloni M On reducing computational overhead in multi-objective genetic Takagi–Sugeno fuzzy systems 2011 Applied Soft Computing   article DOI  
Cordon O, del Jesus MJ, Herrera F, Magdalena L, Villar P A Multiobjective Genetic Learning Process for Joint Feature Selection and Granularity and Context Learning in Fuzzy Rule-Based Classification Systems 2003 in: Interpretability Issues in Fuzzy Modeling, Casillas J, Cordon O, Herrera F, Magdalena L (eds), Springer, 2003Interpretability Issues in Fuzzy Modeling   inbook  
Cordon O, del Jesus MJ, Herrera F, Villar P A Multiobjective Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems 2001 in: Proc. of the joint 9th IFSA World Congress and 20th NAFIPS Int. Conf. (IFSA-NAFIPS'01)   inproceedings  
Cordon O, Gomide F, Herrera F, Hoffmann F, Magdalena L Ten years of genetic fuzzy systems: Current framework and new trends 2004 Fuzzy Sets and Systems   article  
Cordon O, Herrera F, del Jesus MJ, Magdalena L, Sanchez AM, Villar P A Multiobjective Genetic Algorithm for Feature Selection and Data Base Learning in Fuzzy-Rule Based Classification Systems 2002 in: Proc. of the 9th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU'02)   inproceedings  
Cordon O, Quirin A, Sanchez L A First Study on Bagging Fuzzy Rule-based Classication Systems with Multicriteria Genetic Selection of the Component Classiers 2008 in: Proc. of the 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS '08)   inproceedings  
Delgado O, Casillas J Extraccion de conocimiento mediante un algoritmo genetico multiobjetivo estilo Pittsburgh y reglas linguisticas tipo DNF 2007 in Proc. of the 5th Congreso Espanol sobre Metahuristicas, Algoritmos Evolutivos y Bioinspirados (MAEB'07)   inproceedings  
De Vega MA, Bardallo JM, Marquez FA, Peregrin, A Parallel Distributed Two-Level Evolutionary Multiobjective Methodology for Granularity Learning and Membership Functions Tuning in Linguistic Fuzzy Systems 2009 in Proc. of the 9th Int. Conf. on Intelligent Systems Design and Applications (ISDA'09)   inproceedings  
Di Nuovo A, Ascia G, Catania V A Study on Evolutionary Multi-Objective Optimization with Fuzzy Approximation for Computational Expensive Problems 2012 Parallel Problem Solving from Nature - PPSN XII   inbook DOI  
Di Nuovo AG, Catania V Linguistic Modifiers to Improve the Accuracy-Interpretability Trade-off in Multi-Objective Genetic Design of Fuzzy Rule Based Classifier Systems 2009 in Proc. of the 9th Int. Conf. on Intelligent Systems Design and Applications (ISDA'09)   inproceedings  
Ducange P, Lazzerini B, Marcelloni F Multi-objective Genetic Fuzzy Classifiers for Imbalanced and Cost-sensitive Datasets 2010 Soft Computing   article DOI  
Ducange P, Marcelloni F Multi-objective Evolutionary Fuzzy Systems 2011 Fuzzy Logic and Applications   inbook DOI  
Emmanouilidis C, Hunter A, MacIntyre J, Cox C Multiple-criteria genetic algorithms for feature selection in neurofuzzy modeling 1999 in: Proc. of the International Joint Conference on Neural Networks (IJCNN'99)   inproceedings  
Emmanouilidis C, Hunter A, MacIntyre J, Cox C Selecting features in neurofuzzy modelling by multiobjective genetic algorithms 1999 in: Proc. of the 9th Int. Conf. on Artificial Neural Networks (ICANN'99)   inproceedings  
Herrera F Genetic Fuzzy Systems: Taxonomy, Current Research Trends and Prospects 2008 Evolutionary Intelligence   article  
Herrera F Genetic fuzzy systems: Status, critical considerations and future directions 2005 International Journal of Computational Intelligence Research   article  
Fazendeiro P, de Oliveira JV, Pedrycz W A Multiobjective Design of a Patient and Anaesthetist-Friendly Neuromuscular Blockade Controller 2007 IEEE Transactions on Biomedical Engineering   article  
Fazzolari M, Alcala R, Herrera F A multi-objective evolutionary method for learning granularities based on fuzzy discretization to improve the accuracy-complexity trade-off of fuzzy rule-based classification systems: D-MOFARC algorithm 2014 Applied Soft Computing   article DOI  
Fazzolari M, Alcala R, Nojima Y, Ishibuchi H, Herrera F A Review of the Application of Multiobjective Evolutionary Fuzzy Systems: Current Status and Further Directions 2013 IEEE Transactions on Fuzzy Systems   article DOI  
Fazzolari M, Giglio B, Alcala R, Marcelloni F, Herrera F A study on the application of instance selection techniques in genetic fuzzy rule-based classification systems: Accuracy-complexity trade-off 2013 Knowledge-Based Systems   article DOI  
Gacto MJ, Alcala R, Herrera F A Multi-Objective Evolutionary Algorithm for an Effective Tuning of Fuzzy Logic Controllers in Heating, Ventilating and Air Conditioning Systems 2012 Applied Intelligence   article DOI  
Gacto MJ, Alcala R, Herrera F Integration of an index to preserve the semantic interpretability in the multi-objective evolutionary rule selection and tuning of linguistic fuzzy systems 2010 IEEE Transactions on Fuzzy Systems   article  
Gacto MJ, Alcala R, Herrera F Adaptation and Application of Multi-Objective Evolutionary Algorithms for Rule Reduction and Parameter Tuning of Fuzzy Rule-Based Systems 2009 Soft Computing   article  
Gacto MJ, Alcala R, Herrera F A Multiobjective Evolutionary Algorithm for Tuning Fuzzy Rule Based Systems with Measures for Preserving Interpretability 2009 in Proc. of the joint International Fuzzy Systems Association World Congress and the European Society for Fuzzy Logic and Technology Conference (IFSA/EUSFLAT 2009)   inproceedings  
Gacto MJ, Alcala R, Herrera F An Improved Multi-Objective Genetic Algorithm for Tuning Linguistic Fuzzy System 2008 in Proc. of 2008 International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2008)   inproceedings  
Gacto MJ, Alcala R, Herrera F Multi-Objective Genetic Fuzzy Systems: On the Necessity of Including Expert Knowledge in the MOEA Design Process 2008 in Proc. of 2008 International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2008)   inproceedings  
Gacto MJ, Galende M, Alcala R, Herrera F METSK-HDe: A multiobjective evolutionary algorithm to learn accurate TSK-fuzzy systems in high-dimensional and large-scale regression problems 2014 Information Sciences   article DOI  
Galende-Hernandez M, Sainz-Palmero G, Fuente-Aparicio M Complexity reduction and interpretability improvement for fuzzy rule systems based on simple interpretability measures and indices by bi-objective evolutionary rule selection 2012 Soft Computing   article DOI  
Galende M, Gacto MJ, Sainz G, Alcala R Comparison and design of interpretable linguistic vs. scatter FRBSs: Gm3m generalization and new rule meaning index for global assessment and local pseudo-linguistic representation 2014 Information Sciences   article DOI  
Yen GG Multi-objective Evolutionary Algorithm for Temporal Linguistic Rule Extraction 2006 in: Multi-objective Machine Learning, Jin Y. (eds), Springer, 2006Multi-Objective Machine Learning   inbook  
Ghandar A, Michalewicz Z An experimental study of Multi-Objective Evolutionary Algorithms for balancing interpretability and accuracy in fuzzy rulebase classifiers for financial prediction 2011 in Proc. of the 2011 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr)   inproceedings DOI  
Gholamian MR, Fatemi SMT, Ghazanfari M A Hybrid Systematic Design for Multiobjective Market Problems: A Case Study in Crude Oil Markets 2005 Engineering Applications of Artificial Intelligence   article  
Ghosh A, Nath B Multi-Objective Rule Mining Using Genetic Algorithms 2004 Information Sciences   article  
Gladwin D, Stewart P, Parr M, Jill S A Multiobjective G.A./Fuzzy Logic augmented flight controller for an F16 aircraft 2007 in Proc. of the 2007 IEEE International Fuzzy Systems Conference (FUZZ-IEEE'07)   inproceedings  
Gomez-Skarmeta AF, Jimenez F, Ibanez J Pareto-optimality in fuzzy modeling 1997 in Proc. of the 6th European Congress on Int. Tech. Soft Comput.   inproceedings  
Gomez-Skarmeta AF, Jimenez F, Sanchez G Improving interpretability in approximative fuzzy models via multiobjective evolutionary algorithms 2007 International Journal of Intelligent Systems   article  
Gonzalez J, Rojas I, Pomares H, Rojas F, Palomares JM Multi-objective evolution of fuzzy systems 2006 Soft Computing   article  
Gonzalez M, Casillas J, Morell C Dealing with three uncorrelated criteria by many-objective genetic fuzzy systems 2011 Genetic and Evolutionary Fuzzy Systems (GEFS), 2011 IEEE 5th International Workshop on   inproceedings DOI  
Guenounou O, Belmehdi A, Dahhou B Multi-objective optimization of TSK fuzzy models 2009 Expert Systems with Applications   article  
Guenounou O, Belmehdi A, Dahhou B Multi-objective optimization of TSK fuzzy models 2008 in Proc. of the 5th International Multi-Conference on Systems, Signals and Devices   inproceedings  
Ishibuchi H Evolutionary multiobjective design of fuzzy rule-based systems 2007 in: Proc. of the 2007 IEEE Symposium on Foundation of Computational Intelligence   inproceedings  
Ishibuchi H Multiobjective genetic fuzzy systems: review and future research directions 2007 in: Proc. of the 2007 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'07)   inproceedings  
Ishibuchi H Evolutionary multiobjective optimization for fuzzy knowledge extraction 2007 in: Proc. of 8th International Symposium on Advanced Intelligent Systems   inproceedings  
Hamada Y, Nojima Y, Ishibuchi H Use of multi-objective genetic rule selection for examining the effectiveness of inter-vehicle communication in traffic simulations 2009 Artificial Life and Robotics   article  
Huang W, Ding L, Oh S-K Design of Fuzzy Radial Basis Function Neural Networks with the Aid of Multi-objective Optimization Based on Simultaneous Tuning 2011 Advances in Neural Networks ISNN 2011   inbook DOI  
Huang W, Oh S-K Identification of Fuzzy Inference Systems by Means of a Multiobjective Opposition-Based Space Search Algorithm 2013 Mathematical Problems in Engineering   article DOI  
Huang W, Oh S-K, Kim, J-T Design of Information Granulation-Based Fuzzy Models with the Aid of Multi-objective Optimization and Successive Tuning Method 2011 Advances in Neural Networks ISNN 2011   inbook DOI  
Hughes EJ, Tsourdos A, White BA Multiobjective design of a fuzzy controller for a nonlinear missile autopilot 2002 in: Proc. of the IEEE International Symposium on Computer Aided Control System Design (CACSD'02)   inproceedings  
de la Iglesia B, Reynolds A, Rayward-Smith VJ Developments on a Multi-Objective Metaheuristic (MOMH) Algorithm for Finding Interesting Sets of Classification Rules 2005 in: Proc. of the 3rd International Conference on Evolutionary Multi-Criterion Optimization (EMO'05)   inproceedings  
Ishibuchi, Hisao and Nojima, Yusuke Repeated double cross-validation for choosing a single solution in evolutionary multi-objective fuzzy classifier design 2013 Knowledge-Based Systems   article DOI  
Ishibuchi H, Kuwajima I, Nojima Y Use of Pareto-Optimal and Near Pareto-Optimal Candidate Rules in Genetic Fuzzy Rule Selection 2007 in: Analysis and Design of Intelligent Systems using Soft Computing Techniques, Melin, P., Castillo, O., Ramirez, E. G., Kacprzyk, J., Pedrycz, W. (eds), Springer, 2007Analysis and Design of Intelligent Systems using Soft Computing Techniques   inbook  
Ishibuchi H, Kuwajima I, Nojima Y Relation between Pareto-optimal fuzzy rules and Pareto-optimal fuzzy rule sets 2007 in: Proc. of the 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making   inproceedings  
Ishibuchi H, Kuwajima I, Nojima Y Prescreening of candidate rules using association rule mining and Pareto-optimality in genetic rule selection 2007 in: Proc. of 11th International Conference on Knowledge Based Intelligent Information and Engineering Systems (KES'07)   inproceedings  
Ishibuchi H, Murata T Multi-objective genetic local search for minimizing the number of fuzzy rules for pattern classification problems 1998 in: Proc. of the 1998 IEEE International Conference on Fuzzy Systems   inproceedings  
Ishibuchi H, Murata T Minimizing the fuzzy rule base and maximizing its performance by a multi-objective genetic algorithm 1997 in: Proc. of the 1997 IEEE International Conference on Fuzzy Systems   inproceedings  
Ishibuchi H, Murata T, Gen M Performance evaluation of fuzzy rule-based classification systems obtained by multi-objective genetic algorithms 1998 Computers and Industrial Engineering   article  
Ishibuchi H, Murata T, Gen M Performance evaluation of fuzzy rule-based classification systems obtained by multi-objective genetic algorithms 1997 in: Proc. of the 22nd International Conference on Computers and Industrial Engineering   inproceedings  
Ishibuchi H, Murata T, Turksen IB Single-Objective and Two-Objective Genetic Algorithms for Selecting Linguistic Rules for Pattern Classification Problems 1997 Fuzzy Sets and Systems   article  
Ishibuchi H, Murata T, Turksen IB Selecting linguistic classification rules by two-objective genetic algorithms 1995 in: Proc. of the 1995 IEEE International Conference on Systems, Man and Cybernetics   inproceedings  
Ishibuchi H, Nakashima T Three-objective optimization in linguistic function approximation 2001 in: Proc. of the Congress on Evolutionary Computation (CEC 2001)   inproceedings  
Ishibuchi H, Nojima Y Multiobjective Genetic Fuzzy Systems 2015 Springer Handbook of Computational Intelligence   inbook DOI  
Ishibuchi H, Nojima Y Multiobjective Genetic Fuzzy Systems 2009 Computational Intelligence   inbook DOI  
Ishibuchi H, Nojima Y Difficulties in choosing a single final classifier from non-dominated solutions in multiobjective fuzzy genetics-based machine learning 2013 IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013 Joint   inproceedings DOI  
Ishibuchi H, Nojima Y Analysis of interpretability-accuracy tradeoff of fuzzy systems by multiobjective fuzzy genetics-based machine learning 2007 Int. J. of Approximate Reasoning   article  
Ishibuchi H, Nojima Y Evolutionary multiobjective optimization for the design of fuzzy rule-based ensemble classifiers 2006 International Journal of Hybrid Intelligent Systems   article  
Ishibuchi H, Nojima Y Tradeoff between accuracy and rule length in fuzzy rule-based classification systems for high-dimensional problems 2006 in: Proc. of the 11th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems   inproceedings  
Ishibuchi H, Nojima Y Performance evaluation of evolutionary multiobjective approaches to the design of fuzzy rule-based ensemble classifiers 2005 in: Proc. of the 5th International Conference on Hybrid Intelligent Systems   inproceedings  
Ishibuchi H, Nojima Y Multiobjective formulations of fuzzy rule-based classification system design 2005 in: Proc. of the 4th Conference of the European Society for Fuzzy Logic and Technology and 11 Rencontres Francophones sur la Logique Floue et ses Applications   inproceedings  
Ishibuchi H, Nojima Y Multiobjective fuzzy genetics-based machine learning 2005 in: Proc. of the 1st Workshop on Genetic Fuzzy Systems   inproceedings  
Ishibuchi H, Nojima Y Accuracy-complexity tradeoff analysis by multiobjective rule selection 2005 in: Proc. of ICDM'05 Workshop on Computational Intelligence in Data Mining   inproceedings  
Ishibuchi H, Nakashima T, Murata T Multiobjective optimization in linguistic rule extraction from numerical data 2001 in: Proc. of Evolutionary Multi-Criterion Optimization (EMO 2001)   inproceedings  
Ishibuchi H, Nakashima T, Murata T Three-objective genetics-based machine learning for linguistic rule extraction 2001 Information Sciences   article  
Ishibuchi H, Nakashima Y, Nojima Y Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning 2011 Soft Computing   article DOI  
Ishibuchi H, Nakashima Y, Nojima Y Double cross-validation for performance evaluation of multi-objective genetic fuzzy systems 2011 in Proc. of the 5th IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS'11)   inproceedings  
Ishibuchi H, Nakashima Y, Nojima Y Search ability of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetic-based machine learning 2009 in Proc. of the 2009 Int. Conference on Fuzzy Systems (FUZZ-IEEE 2009)   inproceedings  
Ishibuchi H, Nakashima Y, Nojima Y Search ability of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetic-based machine learning 2009 in Proc. of the 18th Int. Conference on Fuzzy Systems (FUZZ-IEEE'09)   inproceedings DOI  
Ishibuchi H, Nojima Y, Kuwajima I Finding simple fuzzy classification systems with high interpretability through multiobjective rule selection 2006 in: Proc. of the Knowledge-Based Intelligent Information and Engineering Systems (KES'06)   inproceedings  
Ishibuchi H, Nojima Y, Kuwajima I Finding simple fuzzy classification systems with high interpretability through multiobjective rule selection 2006 in: Proc. of the 10th International Conference on Knowledge Based Intelligent Information and Engineering Systems   inproceedings  
Ishibuchi H, Nojima Y, Kuwajima I Fuzzy data mining by heuristic rule extraction and multiobjective genetic rule selection 2006 in: Proc. of the 2006 IEEE International Conference on Fuzzy Systems   inproceedings  
Ishibuchi H, Nojima Y, Kuwajima I Multiobjective genetic rule selection as a data mining postprocessing procedure 2006 in: Proc. of the 2006 Genetic and Evolutionary Computation Conference (GECCO'06)   inproceedings  
Ishibuchi H, Sotani T, Murata T Tradeoff between the performance of fuzzy rule-based classification systems and the number of fuzzy if-then rules 1999 in: Proc. of the 18th International Conference of the North American Fuzzy Information Processing Society (NAFIPS 1999)   inproceedings  
Ishibuchi H, Tsukamoto N, Nojima Y Evolutionary Many-Objective Optimization 2008 in: Proc. of 3rd International Workshop on Genetic and Evolving Fuzzy Systems   inproceedings  
Ishibuchi H, Yamamoto T Interpretability issues in fuzzy genetics-based machine learning for linguistic modelling 2003 in: Proc. of Modelling with Words (MWW'03)   inproceedings  
Ishibuchi H, Yamamoto T Evolutionary multiobjective optimization for generating an ensemble of fuzzy rule-based classifiers 2003 in: Proc. of Genetic and Evolutionary Computation (GECCO'03)   inproceedings  
Ishibuchi H, Yamamoto T Effects of three-objective genetic rule selection on the generalization ability of fuzzy rule-based systems 2003 in: Proc. of Evolutionary Multi-Criterion Optimization (EMO'03)   inproceedings  
Ishibuchi H, Yamamoto T Fuzzy rule selection by multi-objective genetic local search algorithms and rule evaluation measures in data mining 2004 Fuzzy Sets and Systems   article  
Ishibuchi H, Yamamoto T Multi-objective evolutionary design of fuzzy rule-based systems 2004 in: Proc. of the 2004 IEEE International Conference on Systems, Man and Cybernetics   inproceedings  
Casillas J Efficient Multi-objective Genetic Tuning of Fuzzy Models for Large-Scale Regression Problems 2009 in Proc. of the 2009 Int. Conf. on Fuzzy Systems (FUZZ-IEEE'09)   inproceedings  
Jimenez F, Gomez-Skarmeta AF, Roubos JA, Babuska R Accurate, transparent and compact fuzzy models for function approximation and dynamic modeling through multi-objective evolutionary optimization 2001 in: Proc. EMO'01: Evolutionary Multi-Criterion Optimization   inproceedings  
Jimenez F, Sanchez G, Gomez-Skarmeta AF, Roubos H, Babuska R Fuzzy modeling with multi-objective neuro-evolutionary algorithms 2002 in: Proc. of the 2002 IEEE Int. Conf. on Systems, Man and Cybernetics   inproceedings  
de Jong A, Cococcioni M NATO Fuzzy Logic Generic Mine Model 2007 in Proc. of the 2007 Undersea Defence Technology Europe Conference (UDT-EUROPE 2007)   inproceedings  
Khalili-Damghani K, Sadi-Nezhad S, Lotfi FH, Tavana M A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection 2013 Information Sciences   article DOI  
Kuwajima I, Nojima Y, Ishibuchi H Effects of constructing fuzzy discretization from crisp discretization for rule-based classifiers 2008 in: Proc. of 13th International Symposium on Artificial Life and Robotics   inproceedings  
Cococcioni M mspMEA: the Microcones Separation Parallel Multiobjective Evolutionary Algorithm and its Application to Fuzzy Rule-Based Ship Classification inpress Recent Advances in Computational Intelligence in Defense and Security   inbook  
Cococcioni M HPFC: High Performance Fuzzy Computing at your desk using GPUs for multi-objective evolutionary optimization of fuzzy systems 2010 Technical Report, Department of Information Engineering, University of Pisa   inbook  
Marquez AA, Marquez FA, Peregrin A A Mechanism to Improve the Interpretability of Linguistic Fuzzy Systems with Adaptive Defuzzification based on the use of a Multi-objective Evolutionary Algorithm 2012 International Journal of Computational Intelligence Systems   article DOI  
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Martinez-Lopez FJ, Casillas J Mining Uncertain Data with Multiobjective Genetic Fuzzy Systems to Be Applied in Consumer Behaviour Modelling 2009 Expert Systems with Applications   article  
Matthews SG, Gongora MA, Hopgood AA Evolving Temporal Fuzzy Association Rules from Quantitative Data with a Multi-Objective Evolutionary Algorithm 2011 Hybrid Artificial Intelligent Systems, Part. I   inbook DOI  
Matthews SG, Gongora MA, Hopgood AA Evolutionary Algorithms and Fuzzy Sets for Discovering Temporal Rules 2013 Applied Mathematics and Computer Science   article DOI  
Matthews SG, Gongora MA, Hopgood AA Evolving Temporal Fuzzy Itemsets from Quantitative Data with a Multi-Objective Evolutionary Algorithm 2011 Genetic and Evolutionary Fuzzy Systems (GEFS), 2011 IEEE 5th International Workshop on   inproceedings DOI  
Munoz-Salinas R, Aguirre E, Cordon O, Garcia-Silvente M Automatic Tuning of a Fuzzy Visual System Using Evolutionary Algorithms: Single-objective vs. Multiobjective Approaches 2008 IEEE Transactions on Fuzzy Systems   article  
Munoz-Salinas R, Aguirre EO, Garcia-Silvente M, Gonzalez A Tuning a visual fuzzy system using SPEA2 2005 in: Proc. of the 1st International Workshop on Genetic Fuzzy Systems (GFS'05)   inproceedings  
Narukawa K, Nojima Y, Ishibuchi H Modification of evolutionary multiobjective optimization algorithms for multiobjective design of fuzzy rule-based classification systems 2005 in: Proc. of 2005 IEEE Int. Conf. on Fuzzy Systems   inproceedings  
Nojima Y, Ishibuchi H Incorporation of user preference into multiobjective genetic fuzzy rule selection for pattern classification problems 2009 Artificial Life and Robotics   article  
Nojima Y, Ishibuchi H Interactive genetic fuzzy rule selection through evolutionary multiobjective optimization with user preference 2009 in Proc. of 2009 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making (MCDM'09)   inproceedings  
Nojima Y, Ishibuchi H Interpretability-accuracy tradeoff by multiobjective genetics-based machine learning for pattern classification problems 2006 in: Proc. of the 11th International Symposium on Artificial Life and Robotics   inproceedings  
Nojima Y, Ishibuchi H Designing fuzzy ensemble classifiers by evolutionary multiobjective optimization with an entropy-based diversity criterion 2006 in: Proc. of the 6th International Conference on Hybrid Intelligent Systems and 4th Conference on Neuro-Computing and Evolving Intelligence   inproceedings  
Nojima Y, Ishibuchi H Comparison between single-objective and multi-objective formulations for fuzzy rule-based classification system design 2005 in: Proc. of the 5th Asian Symposium on Applied Electromagnetics and Mechanics   inproceedings  
Nojima Y, Takahashi Y, Ishibuchi H Application of Parallel Distributed Implementation to Multiobjective Fuzzy Genetics-Based Machine Learning 2015 Intelligent Information and Database Systems   inbook DOI  
Nojima Y, Takahashi Y, Ishibuchi H Genetic lateral tuning of membership functions as post-processing for hybrid fuzzy genetics-based machine learning 2014 Soft Computing and Intelligent Systems (SCIS), 2014 Joint 7th International Conference on and Advanced Intelligent Systems (ISIS), 15th International Symposium on   inproceedings DOI  
Nojima Y, Watanabe K, Ishibuchi H Effects of heuristic rule generation from multiple patterns in multiobjective fuzzy genetics-Based machine learning 2015 Evolutionary Computation (CEC), 2015 IEEE Congress on   inproceedings DOI  
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Omar HM, Abido MA Multiobjective Evolutionary Algorithm for Designing Fuzzy-Based Missile Guidance Laws 2011 Journal of Aerospace Engineering   article DOI  
Phooi K, Ming K Nonlinear Time Series Prediction Based on Lyapunov Theory-Based Fuzzy Neural Network and Multiobjective Genetic Algorithm 2003 in: Proc. of the 16th Australian Conference on AI (Advances in Artificial Intelligence) (AI'03)   inproceedings  
Pulkkinen, P., Koivisto, H. A Genetic Fuzzy System With Inconsistent Rule Removal and Decision Tree Initialization 2009 Applications of Soft Computing: From Theory to Praxis   inbook  
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Yamamoto T, Ishibuchi H Performance evaluation of three-objective genetic rule selection 2003 in: Proc. of the 2003 IEEE International Conference on Fuzzy Systems   inproceedings  
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