私たちは進化計算,ファジィシステム,ニューラルネットワーク,強化学習,人工生命など, 計算知能あるいはソフト・コンピューティングと総称される枠組を用いた知的コンピュータシステムの開発に取り組んでいます.

Downloadable Papers

If you want other papers, please contact me by e-mail.


Accepted


H. Ishibuchi, L. M. Pang, and K. Shang, "Difficulties in fair performance comparison of multi-objective evolutionary algorithms [research frontier]," IEEE Computational Intelligence Magazine, vol. 17, no. 1, pp. 86-101, Feb. 2022. Pre-print PDF


Open Access Paper (IEEE Trans.)


H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima, "Reference point specification in inverted generational distance for triangular linear Pareto front," IEEE Trans. on Evolutionary Computation (in press)
[Reference Data and Code]

H. Ishibuchi, Y. Setoguchi, H. Masuda, and Y. Nojima, "Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes," IEEE Trans. on Evolutionary Computation, vol. 21, no.2, pp. 169-190, April 2017.
[Pareto Front Data]

H. Ishibuchi, N. Akedo, and Y. Nojima, "Behavior of multi-objective evolutionary algorithms on many-objective knapsack problems," IEEE Trans. on Evolutionary Computation, vol 19, no. 2, pp. 264-283, 2015.
[Knapsack Problem Data]

H. Ishibuchi, S. Mihara, Y. Nojima: Parallel Distributed Hybrid Fuzzy GBML Models With Rule Set Migration and Training Data Rotation, IEEE Trans. on Fuzzy Systems, vol. 21, no. 2, pp. 355-368, 2013.


Book Chapters for Edited Books


H. Ishibuchi and T. Yoshida, "Hybrid Evolutionary Multi-Objective Optimization Algorithms," in A. Abraham et al.(eds.): Soft Computing Systems: Design, Management and Applications (Frontiers in Artificial Intelligence and Applications, Volume 87), pp. 163-172, 2002. PDF


Journal Papers


H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima, “How to specify a reference point in hypervolume calculation for fair performance comparison,” Evolutionary Computation, 2018 (Accepted) PDF

H. Ishibuchi, K. Doi, and Y. Nojima, “On the effect of normalization in MOEA/D for multi-objective and many-objective optimization,” Complex & Intelligent Systems, 2017 (Open Access) (DOI 10.1007/s40747-017-0061-9)

H. Ishibuchi, H. Masuda, and Y. Nojima, "Pareto fronts of many-objective degenerate test problems," IEEE Trans. on Evolutionary Computation, vol. 20, no. 5, pp. 807-813, October 2016. PDF

H. Ishibuchi, T. Sudo, and Y. Nojima, "Interactive evolutionary computation with minimum fitness evaluation requirement and offline algorithm design," SpringerPlus, vol. 5, Paper No. 192, Total 29 pages. February 2016. (Online Journal) doi:10.1186/s40064-016-1789-1

H. Ishibuchi, N. Akedo, and Y. Nojima, "Behavior of multi-objective evolutionary algorithms on many-objective knapsack problems," IEEE Trans. on Evolutionary Computation, vol 19, no. 2, pp. 264-283, 2015.

H. Ishibuchi and Y. Nojima, "Repeated double cross-validation for choosing a single solution in evolutionary multi-objective fuzzy classifier design," Knowledge-Based Systems, vol. 54, pp. 22-31, December 2013. PDF

H. Ishibuchi, S. Mihara, Y. Nojima: Parallel Distributed Hybrid Fuzzy GBML Models With Rule Set Migration and Training Data Rotation, IEEE Trans. on Fuzzy Systems, vol. 21, no. 2, pp. 355-368, 2013.

H. Ishibuchi, H. Ohyanagi, and Y. Nojima, "Evolution of strategies with different representation schemes in a spatial iterated prisoner's dilemma game," IEEE Trans. on Computational Intelligence and AI in Games, vol. 3, no. 1, pp. 67-82, March 2011. PDF

H. Ishibuchi, N. Tsukamoto, and Y. Nojima, "Diversity Improvement by Non-Geometric Binary Crossover in Evolutionary Multiobjective Optimization," IEEE Transactions on Evolutionary Computation, vol. 14, no. 6, pp. 985-998, December 2010. PDF

Y. Nojima, H. Ishibuchi, and I. Kuwajima, "Parallel Distributed Genetic Fuzzy Rule Selection," Soft Computing, vol. 13, no. 5, pp. 511-519, March 2009. PDF

H. Ishibuchi, Y. Hitotsuyanagi, N. Tsukamoto, and Y. Nojima, "Use of Biased Neighborhood Structures in Multi-Objective Memetic Algorithms," Soft Computing, vol. 13, no. 8-9, pp. 795-810, July 2009. PDF

H. Ishibuchi, K. Narukawa, N. Tsukamoto, and Y. Nojima, "An Empirical Study on Similarity-Based Mating for Evolutionary Multiobjective Combinatorial Optimization," European Journal of Operational Researchh, vol. 188, no. 1, pp. 57-75, July 2008. PDF

H. Ishibuchi and N. Namikawa, "Evolution of Iterated Prisoner's Dilemma Game Strategies in Structured Demes under Random Pairing in Game-Playing," IEEE Trans. on Evolutionary Computation, Vol. 9, No. 6, pp. 552-561, December 2005. PDF

H. Ishibuchi, T. Yamamoto, and T. Nakashima, "An Approach to Fuzzy Default Reasoning for Function Approximation," Soft Computing, Vol. 10, No. 9, pp. 850-864, July 2006. PDF

H. Ishibuchi and Y. Nojima, "Analysis of Interpretability-Accuracy Tradeoff of Fuzzy Systems by Multiobjective Fuzzy Genetics-Based Machine Learning," International Journal of Approximate Reasoning, vol. 44, no. 1, pp. 4-31, January 2007. PDF

H. Ishibuchi and T. Yamamoto, "Rule Weight Specification in Fuzzy Rule-Based Classification Systems," IEEE Trans. on Fuzzy Systems, Vol. 13, No. 4, pp. 428-435, August 2005. PDF

H. Ishibuchi, T. Yamamoto, and T. Nakashima, "Hybridization of Fuzzy GBML Approaches for Pattern Classification Problems," IEEE Trans. on Systems, Man, and Cybernetics- Part B: Cybernetics, Vol. 35, No. 2, pp. 359- 365, April 2005. PDF

H. Ishibuchi and T. Yamamoto, "Comparison of Heuristic Criteria for Fuzzy Rule Selection in Classification Problems," Fuzzy Optimization and Decision Making, Vol. 3, no. 2, pp. 119-139, June 2004. PDF

H. Ishibuchi and T. Yamamoto, "Fuzzy Rule Selection by Multi-Objective Genetic Local Search Algorithms and Rule Evaluation Measures in Data Mining," Fuzzy Sets and Systems, Vol. 141, no. 1, pp. 59-88, January 2004. PDF

H. Ishibuchi, T. Yoshida, and T. Murata, " Balance between Genetic Search and Local Search in Memetic Algorithms for Multiobjective Permutation Flowshop Scheduling ," IEEE Trans. on Evolutionary Computation, Vol. 7, No. 2, pp.204-223, April 2003. PDF

H. Ishibuchi, R. Sakamoto, and T. Nakashima, " Learning Fuzzy Rules from Iterative Execution of Games ," Fuzzy Sets and Systems, Vol. 135, No. 2, pp. 213-240, April 2003. PDF

H. Ishibuchi, R. Sakamoto, and T. Nakashima, " Evolution of unplanned coordination in a market selection game ," IEEE Trans. on Evolutionary Computation, Vol. 5, No. 5, pp. 524-534, October 2001. PDF

H. Ishibuchi and T. Nakashima, "Effect of rule weights in fuzzy rule-based classification systems," IEEE Trans. on Fuzzy Systems, Vol. 9, No. 4, pp. 506-515, August 2001. PDF

H. Ishibuchi, T. Nakashima and T. Murata, "Three-objective genetics-based machine learning for linguistic rule extraction," Information Sciences, Vol. 136, No. 1-4, pp. 109-133, August 2001. PDF

H. Ishibuchi and H. Tanaka, "Multiobjective programming in optimization of the interval objective function," European Journal of Operational Research, Vol. 48, No. 2, pp. 219-225, September 1990.
For a PDF file, please send an e-mail to me


Conference Papers


H. Ishibuchi, T. Matsumoto, N. Masuyama, and Y. Nojima, "Many-objective problems are not always difficult for Pareto dominance-based evolutionary algorithms," Proc. of European Conference on Artificial Intelligence 2020 PDF
-->[Related Materials]

H. Ishibuchi, T. Matsumoto, N. Masuyama, and Y. Nojima, “Effects of dominance resistant solutions on the performance of evolutionary multi-objective and many-objective algorithms,” Proc. of 2020 Genetic and Evolutionary Computation Conference PDF

H. Ishibuchi, R. Imada, Y. Setoguchi and Y. Nojima, “Hypervolume subset selection for triangular and inverted triangular Pareto fronts of three-objective problems,” Proc. of The 14th ACM/SIGEVO Workshop on Foundations of Genetic Algorithms, pp. 95-110, Copenhagen, Denmark, January 12-15, 2017. PDF

Y. Nojima, Y. Tanigaki, and H. Ishibuchi, “Multiobjective data mining from solutions by evolutionary multiobjective optimization,” Proc. of 2017 Genetic and Evolutionary Computation Conference, pp. 617-624, Berlin, Germany, July 15-19, 2017. PDF

H. Ishibuchi, R. Imada, Y. Setoguchi, and Y. Nojima, “Reference point specification in hypervolume calculation for fair comparison and efficient search,” Proc. of 2017 Genetic and Evolutionary Computation Conference, pp. 585-592, Berlin, Germany, July 15-19, 2017. PDF

Y. Nojima and H. Ishibuchi, “Multiobjective fuzzy genetics-based machine learning with a reject option,” Proc. of 2016 IEEE International Conference on Fuzzy Systems, pp. 1405-1412, Vancouver, Canada, July 24-29, 2016. PDF

H. Ishibuchi, R. Imada, Y. Setoguchi and Y. Nojima, “Performance comparison of NSGA-II and NSGA-III on various many-objective test problems,” Proc. of 2016 IEEE Congress on Evolutionary Computation, pp. 3045-3052, Vancouver, Canada, July 24-29, 2016. PDF

H. Masuda, Y. Nojima, and H. Ishibuchi, “Common properties of scalable multiobjective problems and a new framework of test problems,” Proc. of 2016 IEEE Congress on Evolutionary Computation, pp. 3011-3018, Vancouver, Canada, July 24-29, 2016. PDF

Y. Tanigaki, Y. Nojima, and H. Ishibuchi, “Meta-optimization based multi-objective test problem generation using WFG toolkit,” Proc. of 2016 IEEE Congress on Evolutionary Computation, pp. 2768-2775, Vancouver, Canada, July 24-29, 2016. PDF

Y. Nojima and H. Ishibuchi, “Effects of parallel distributed implementation on the search performance of Pittsburgh-style genetics-based machine learning algorithms,” Proc. of 2016 IEEE Congress on Evolutionary Computation, pp. 2193-2200, Vancouver, Canada, July 24-29, 2016. PDF

H. Ishibuchi, Y. Setoguchi, H. Masuda and Y. Nojima, “How to compare many-objective algorithms under different settings of population and archive sizes,” Proc. of 2016 IEEE Congress on Evolutionary Computation, pp. 1149-1156, Vancouver, Canada, July 24-29, 2016. PDF

H. Ishibuchi, K. Doi, and Y. Nojima, “Characteristics of many-objective test problems and penalty parameter specification in MOEA/D,” Proc. of 2016 IEEE Congress on Evolutionary Computation, pp. 1115-1122, Vancouver, Canada, July 24-29, 2016. PDF

H. Ishibuchi, H. Masuda, and Y. Nojima, “Sensitivity of performance evaluation results by inverted generational distance to reference points,” Proc. of 2016 IEEE Congress on Evolutionary Computation, pp. 1107-1114, Vancouver, Canada, July 24-29, 2016. PDF

T. Sudo, K. Goto, Y. Nojima, and H. Ishibuchi, “Further analysis on strange evolution behavior of 7-bit binary string strategies in iterated prisoner’s dilemma game,” Proc. of 2016 IEEE Congress on Evolutionary Computation, pp. 335-342, Vancouver, Canada, July 24-29, 2016. PDF

H. Ishibuchi, K. Doi, H. Masuda, and Y. Nojima, "Relation between weight vectors and solutions in MOEA/D," Proc. of 2015 IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making, pp. 861-868, Cape Town, Decembber 8-10, 2015. PDF

H. Ishibuchi and Y. Nojima, “Handling a training dataset as a black-box model for privacy preserving in fuzzy GBML algorithms,” Proc. of 2015 IEEE International Conference on Fuzzy Systems, 8 pages, Istanbul, Turkey, August 2-5, 2015. PDF

H. Ishibuchi, H. Masuda, and Y. Nojima, “A study on performance evaluation ability of a modified inverted generational distance indicator,” Proc. of Genetic and Evolutionary Computation Conference, pp. 695-702, Madrid, Spain, July 11-15, 2015. PDF

T. Sudo, K. Goto, Y. Nojima, and H. Ishibuchi, “Strange evolution behavior of 7-bit binary string strategies in iterated prisoner’s dilemma game,” Proc. of 2015 IEEE Congress on Evolutionary Computation, pp. 3346-3353, Sendai, Japan, May 25-28, 2015. PDF

H. Ishibuchi, H. Masuda, and Y. Nojima, "Comparing solution sets of different size in evolutionary many-objective optimization," Proc. of 2015 IEEE Congress on Evolutionary Computation, pp. 2859-2866, Sendai, Japan, May 25-28, 2015. PDF

T. Sudo, K. Goto, Y. Nojima, and H. Ishibuchi, “Effects of ensemble action selection with different usage of player’s memory resource on the evolution of cooperative strategies for iterated prisoner’s dilemma game,” Proc. of 2015 IEEE Congress on Evolutionary Computation, pp. 1505-1512, Sendai, Japan, May 25-28, 2015. PDF

H. Ishibuchi, H. Masuda, Y. Tanigaki and Y. Nojima, “Modified distance calculation in generational distance and inverted generational distance,” Proc. of 8th International Conference on Evolutionary Multi-Criterion Optimization, Part I, pp. 110-125, Guimarães, Portugal, March 29-April 1, 2015. PDF

H. Ishibuchi, H. Masuda, Y. Tanigaki, and Y. Nojima, “Review of coevolutionary developments of evolutionary multi-objective and many-objective algorithms and test problems,” Proc. of 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, pp. 178-185, Orlando, Florida, USA, December 9-12, 2014. PDF

H. Ishibuchi, H. Masuda, Y. Tanigaki, and Y. Nojima, “Difficulties in specifying reference points to calculate the inverted generational distance for many-objective optimization problems,” Proc. of 2014 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, pp. 170-177, Orlando, Florida, USA, December 9-12, 2014. PDF

H. Ishibuchi, N. Akedo, and Y. Nojima, "Relation between neighborhood size and MOEA/D performance on many-objective problems," Lecture Notes in Computer Science 7811: Evolutionary Multi-Criterion Optimization - EMO 2013, pp. 459-474, Springer, Berlin, March 2013. PDF

H. Ishibuchi, M. Yamane, and Y. Nojima, "Difficulty in evolutionary multiobjective optimization of discrete objective functions with different granularities," Lecture Notes in Computer Science 7811: Evolutionary Multi-Criterion Optimization - EMO 2013, pp. 230-245, Springer, Berlin, March 2013. PDF

H. Ishibuchi, N. Akedo, and Y. Nojima, "A study on the specification of a scalarizing function in MOEA/D for many-objective knapsack problems," Lecture Notes in Computer Science Volume 7997: Learning and Intelligent Optimization – LION 7, pp. 231-246, Springer, January 2013. PDF

H. Ishibuchi, M. Yamane, and Y. Nojima, "Ensemble fuzzy rule-based classifier design by parallel distributed fuzzy GBML algorithms," Lecture Notes in Computer Science 7673: Simulated Evolution and Learning (9th International Conference on Simulated Evolution and Learning), pp. 93-103, Springer, Berlin, December 16-19, 2012. PDF

H. Ishibuchi, M. Yamane, N. Akedo, and Y. Nojima, "Two-objective solution set optimization to maximize hypervolume and decision space diversity in multiobjective optimization," Proc. of Joint 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligent Systems, pp. 1871-1876, Kobe, Japan, November 20-24, 2012. PDF

H. Ishibuchi, N. Akedo, and Y. Nojima, "Recombination of similar parents in SMS-EMOA on many-objective 0/1 knapsack problems," Proc. of 12th International Conference on Parallel Problem Solving from Nature, Part II, pp. 132-142, Taormina, Italy, September 1-5, 2012. PDF

H. Ishibuchi, K. Hoshino, and Y. Nojima, "Evolution of strategies in a spatial IPD Game with a number of different representation schemes," Proc. of 2012 IEEE Congress on Evolutionary Computation, pp. 808-815, Brisbane, Australia, June, 10-15, 2012. PDF

H. Ishibuchi, K. Hoshino, and Y. Nojima, "Strategy evolution in a spatial IPD game where each agent is not allowed to play against itself," Proc. of 2012 IEEE Congress on Evolutionary Computation, pp. 688-695, Brisbane, Australia, June, 10-15, 2012. PDF

H. Ishibuchi, M. Yamane, and Y. Nojima, "Effects of discrete objective functions with different granularities on the search behavior of EMO algorithms," Proc. of 2012 Genetic and Evolutionary Computation Conference, pp. 481-488, Philadelphia, USA, July 7-11, 2012. PDF

H. Ishibuchi, N. Akedo, and Y. Nojima, "A many-objective test problem for visually examining diversity maintenance behavior in a decision space," Proc. of 2011 Genetic and Evolutionary Computation Conference - GECCO 2011, pp. 649-656, Dublin, Ireland, July 12-16, 2011. PDF

H. Ishibuchi, N. Akedo, H. Ohyanagi, and Y. Nojima, "Behavior of EMO algorithms on many-objective optimization problems with correlated objectives," Proc. of 2011 IEEE Congress on Evolutionary Computation, pp. 1465-1472, New Orleans, June 5-8, 2011. PDF

H. Ishibuchi, Y. Hitotsuyanagi, H. Ohyanagi, and Y. Nojima, "Effects of the Existence of Highly Correlated Objectives on the Behavior of MOEA/D," Lecture Notes in Computer Science 6576: Evolutionary Multi-Criterion Optimization - EMO 2011, pp. 166-181, Ouro Preto, Brazil, April 5-8, 2011. PDF

H. Ishibuchi, Y. Hitotsuyanagi, N. Tsukamoto, and Y. Nojima, "many-Objective Test Problems to Visually Examine the Behavior of Multiobjective Evolution in a Decision Space," Lecture Notes in Computer Science 6239: Parallel Problem Solving from Nature - PPSN XI, part II, pp. 91-100, Springer, Berlin, September 2010. PDF

H. Ishibuchi, Y. Hitotsuyanagi, Y. Wakamatsu, and Y. Nojima, "How to Choose Solutions for Local Search in Multiobjective Combinatorial Memetic Algorithms," Lecture Notes in Computer Science 6238: Parallel Problem Solving from Nature - PPSN XI, part I, pp. 516-525, Springer, Berlin, September 2010. PDF

H. Ishibuchi, Y. Sakane, N. Tsukamoto and Y. Nojima, "Simultaneous use of different scalarizing functions in MOEA/D," Proc. of Genetic and Evolutionary Computation Conference - GECCO 2010, pp. 519-526, Portland, USA, July 7-11, 2010. PDF

H. Ishibuchi, Y. Sakane, N. Tsukamoto, and Y. Nojima, "Selecting a small number of representative non-dominated solutions by a hypervolume-based solution selection approach," Proc. of 2009 IEEE International Conference on Fuzzy Systems, pp. 1609-1614, Jeju Island, Korea, August 20-24, 2009. PDF

H. Ishibuchi, Y. Sakane, N. Tsukamoto, and Y. Nojima, "Single-objective and multi-objective formulations of solution selection for hypervolume maximization," Proc. of 2009 Genetic and Evolutionary Computation Conference, pp. 1831-1832, Montreal, Canada, July 8-12, 2009. PDF

H. Ishibuchi, N. Tsukamoto, and Y. Nojima, "Evolutionary many-objective optimization: A short review," Proc. of 2008 IEEE Congress on Evolutionary Computation, pp. 2424-2431, Hong Kong, June 1-6, 2008. PDF

H. Ishibuchi, "Multiobjective genetic fuzzy systems: Review and future research directions," Proc. of 2007 IEEE International Conference on Fuzzy Systems, pp. 913-918, London, UK, July 23-26, 2007. PDF

H. Ishibuchi and Y. Nojima, "Optimization of scalarizing functions through evolutionary multiobjective optimization," Lecture Notes in Computer Science 4403: Evolutionary Multi-Criterion Optimization - EMO 2007, pp. 51-65, Springer, Berlin, 2007. PDF

H. Ishibuchi, T. Doi, and Y. Nojima, "Effects of using two neighborhood structures in cellular genetic algorithms for function optimization," Lecture Notes in Computer Science 4193: Parallel Problem Solving from Nature - PPSN IX, pp. 949-958, Springer, Berlin, September 2006. PDF

H. Ishibuchi, T. Doi, and Y. Nojima, "Incorporation of scalarizing fitness functions into evolutionary multiobjective optimization algorithms," Lecture Notes in Computer Science 4193: Parallel Problem Solving from Nature - PPSN IX, pp. 493-502, Springer, Berlin, September 2006. PDF

H. Ishibuchi, S. Kaige, and K. Narukawa, "Comparison between Lamarckian and Baldwinian Repair on Multiobjective 0/1 Knapsack Problems," Proc. of the 3rd International Conference on Evolutionary Multi-Criterion Optimization (Guanajuato, Mexico), pp. 370-385, (March 9-11, 2005). PDF

Y. Nojima, K. Narukawa, S. Kaige, and H. Ishibuchi, "Effects of Removing Overlapping Solutions on the Performance of the NSGA-II Algorithm," Proc. of the 3rd International Conference on Evolutionary Multi-Criterion Optimization (Guanajuato, Mexico), pp. 341-354, (March 9-11, 2005). PDF

H. Ishibuchi and K. Narukawa, "Recombination of similar parents in EMO algorithms," Lecture Notes in Computer Science 3410: Evolutionary Multi-Criterion Optimization, pp. 265-279, Springer, Berlin, March 2005. PDF

H. Ishibuchi and Y. Shibata, "Mating scheme for controlling the diversity-convergence balance for multiobjective optimization," Lecture Notes in Computer Science 3102: Genetic and Evolutionary Computation - GECCO 2004, pp. 1259-1271, Springer, Berlin, June 2004. PDF

H. Ishibuchi and T. Yamamoto, "Evolutionary Multiobjective Optimization for Generating an Ensemble of Fuzzy Rule-Based Classifiers," Proc. of 2003 Genetic and Evolutionary Computation Conference (Chicago, USA), pp. 1077-1088, (July 12-16, 2003). PDF

H. Ishibuchi and T. Yoshida, "Hybrid Evolutionary Multi-Objective Optimization Algorithms," Proc. of Second International Conference on Hybrid Intelligent Systems (Santiago, Chile), pp. 163-172, 2002. PDF

H. Ishibuchi and Y. Shibata, "An empirical study on the effect of mating restriction on the search ability of EMO algorithms," Lecture Notes in Computer Science 2632: Evolutionary Multi-Criterion Optimization, pp. 433-447, Springer, Berlin, April 2003. PDF

H. Ishibuchi and T. Yamamoto, "Effects of three-objective genetic rule selection on the generalization ability of fuzzy rule-based systems," Lecture Notes in Computer Science 2632: Evolutionary Multi-Criterion Optimization, pp. 608-622, Springer, Berlin, April 2003. PDF

H. Ishibuchi and T. Yoshida, "Hybrid Evolutionary Multi-Objective Optimization Algorithms," Proc. of Second International Conference on Hybrid Intelligent Systems (Santiago, Chile), pp. 163-172, 2002. PDF

H. Ishibuchi, T. Yoshida, and T. Murata, "Balance between genetic search and local search in hybrid evolutionary multi-criteion optimization algorithms," Proc. of Genetic and Evolutionary Computation Conference (GECCO 2002), pp. 1301-1308, New York, July 9-13, 2002. PDF

H. Ishibuchi and T. Yamamoto, "Fuzzy rule selection by data mining criteria and genetic algorithms," Proc. of Genetic and Evolutionary Computation Conference (GECCO 2002), pp. 399-406, New York, July 9-13, 2002. PDF

T. Murata, H. Ishibuchi, and M. Gen, "Specification of genetic search directions in cellular multi-objective genetic algorithms," Proc. of First International Conference on Evolutionary multi-criterion optimization (Zurich, Switzerland, March 7-9, 2001), pp. 82-95. PDF

H. Ishibuchi, T. Nakashima, "Multi-objective pattern and feature selection by a genetic algorithm," Proc. of Genetic and Evolutionary Computation Conference (Las Vegas, Nevada, U.S.A.), pp. 1069-1076, (July 8-12, 2000). PDF

T. Murata and H. Ishibuchi, "MOGA: Multi-objective genetic algorithms," Proc. of 1995 IEEE International Conference on Evolutionary Computation, pp. 289-294, Perth, Australia, November 1995. PDF

H. Ishibuchi, T. Murata, and I. B. Turksen, "Selecting linguistic classification rules by two-objective genetic algorithms," Proc. of 1995 IEEE International Conference on Systems, Man and Cybernetics, pp. 1410-1415, Vancouver, Canada, October 1995. PDF