日本語
Hiroshima City University 
Graduate School of Information Sciences 
Dept. of Intelligent Systems 

Professor 
Takahama Tetsuyuki 

Tel.082-830-1698  
 
My website is here.  

Academic background
Kyoto University  Faculty of Engineering  電気工学第二学科  1982  Graduated 
Kyoto University  Graduate School, Division of Engineering  電気工学第二専攻  Doctor course  1987  Withdrawn after completion of required course credits 

Academic degrees
Master of Engineering  Kyoto University 
Doctor of Engineering  Kyoto University 

Research Areas
Computational Intelligence 
Evolutionary Computation 
Optimization 

Research keywords
Natural Computing 
Evolutionary Algorithms 
Optimization Algorithms 

Subject of research
Learning Fuzzy Control Rules  1990-Present 
Multiobjective optimization method  1996-Present 
Solving Constrained Optimization Problems by Alpha Constrained Methods  1997-Present 
Structural Learning by Degeneration  1999-Present 

Bibliography
"A Study on Selecting an Oblique Coordinate System for Rotation-Invariant Blend Crossover in a Real-Coded Genetic Algorithm", in Recent Studies in Economic Sciences: Information Systems, Project Managements, Economics, OR and Mathematics  Setsuko Sakai and Tetsuyuki Takahama  65-87  Kyushu University Press  2018/03  Differential Evolution (DE) has been successfully applied to various optimization problems. The performance of DE is affected by algorithm parameters such as a scaling factor F and a crossover rate CR. Many studies have been done to control the parameters adaptively. One of the most successful studies on controlling the parameters is JADE. In JADE, the values of each parameter are generated according to one probability density function (PDF) which is learned by the values in success cases where the child is better than the parent. However, search performance might be improved by learning multiple PDFs for each parameter based on some characteristics of search points. In this study, search points are divided into plural groups according to some criteria and PDFs are learned by parameter values in success cases for each group. Objective values and distances from a reference point, which is the best search point or the centroid of search points, are adopted as the criteria. The effect of JADE with group-based learning is shown by solving thirteen benchmark problems. 
"A Comparative Study on Grouping Methods for an Adaptive Differential Evolution", in Challenging Researches in Economic Sciences: Legal Informatics, Environmental Economics, Economics, OR and Mathematics  Setsuko Sakai and Tetsuyuki Takahama  51-91  Kyushu University Press  2017/03  Differential Evolution (DE) has been successfully applied to various optimization problems. The performance of DE is affected by algorithm parameters such as a scaling factor F and a crossover rate CR. Many studies have been done to control the parameters adaptively. One of the most successful studies on controlling the parameters is JADE. In JADE, the values of each parameter are generated according to one probability density function (PDF) which is learned by the values in success cases where the child is better than the parent. However, search performance might be improved by learning multiple PDFs for each parameter based on some characteristics of search points. In this study, search points are divided into plural groups according to some criteria and PDFs are learned by parameter values in success cases for each group. Objective values and distances from a reference point, which is the best search point or the centroid of search points, are adopted as the criteria. The effect of JADE with group-based learning is shown by solving thirteen benchmark problems. 
"A Comparative Study on Detecting Ridge Structure for Population-Based Optimization Algorithms", in Contemporary Works in Economic Sciences: Legal Informatics, Economics, OR and Mathematics  Setsuko Sakai, Tetsuyuki Takahama  61-82  Kyushu University Press  2016/02 
"A Study on Adaptive Parameter Control for Interactive Differential Evolution Using Pairwise Comparison", in New Solutions in Legal Informatics, Economic Sciences and Mathematics  Setsuko Sakai, Tetsuyuki Takahama  101-121  Kyushu University Press  2015/03 
"A Comparative Study on Estimation Methods of Landscape Modality for Evolutionary Algorithms" in Legal Informatics, Economic Science and Mathematical Research  Setsuko Sakai, Tetsuyuki Takahama  55-80  Kyushu University Press  2014/03 
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Papers
Research paper (scientific journal)  Joint  Particle swarm optimisation with dynamic search strategies based on rank correlation  T.Nishio, J.Kushida, A.Hara, T.Takahama  International Journal of Computational Intelligence Studies  6/ 4, 311-332  2018/01 
Research paper (scientific journal)  Joint  Particle Swarm Optimization with Mutation Operations Controlled by Landscape Modality Estimation using Hill-Valley Detection  T.Takahama, S.Sakai, J. Kuashida and A. Hara  Artificial Life and Robotics  21/ 4, 423-433  2016/12 
Research paper (scientific journal)  Joint  Estimating Landscape Modality of Objective Functions using Rank Correlation for Evolutionary Algorithms  Jun-ichi Kushida, Akira Hara, Tetsuyuki Takahama  Journal of the Japanese Society for Evolutionary Computation  7/ 2, 32-45  2016/11 
Research paper (scientific journal)  Joint  Improving an Adaptive Differential Evolution Using Hill-Valley Detection  Tetsuyuki Takahama and Setsuko Sakai  International Journal of Hybrid Intelligent Systems  13/ 1, 1-13  2016/03 
Research paper (scientific journal)  Joint  NCRDE: Improving Differential Evolution Based on Distance of Individuals and Ranking Information  Jun-ichi Kushida, Akira Hara, Tetsuyuki Takahama  The Transactions of the Institute of Electronics, Information and Communication Engineers (IEICE)  J97-D/ 10, 1604-1615  2014/10 
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Research presentations
Oral presentation(general)  変数間依存性を解消する変換を導入したブレンド交叉の提案  京都大学数理解析研究所RIMS共同研究(公開型)「不確実性の下での意思決定理論とその応用 :計画数学の展開」  2017/11/15 
Oral presentation(general)  Particle Swarm Optimization with the Velocity Updating Rule According to an Oblique Coordinate System  The 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM2017)  2017/10/30 
Oral presentation(general)  An Adaptive Differential Evolution with Exploitation and Exploration by Extreme Individuals  SICE Annual Conference 2017 (SICE2017)  2017/09/22 
Oral presentation(general)  An Adaptive Differential Evolution with Learning Parameters According to Groups Defined by the Rank of Objective Values  The Eighth International Conference on Swarm Intelligence (ICSI2017)  2017/07/27 
Oral presentation(general)  斜交座標系に基づく回転不変なブレンド交叉の提案  情報処理学会 第113回数理モデル化と問題解決研究会  2017/06/24 
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Prizes
IEEE Computational Intelligence Society, CEC2010 Constrained Real-Parameter Optimisation Competition Award  2010/07 
2006 IEEE Congress on Evolutionary Computation Competition Program Award -- Nonlinear Programming  2006/07 
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Allotted class
機械学習特論 
データ構造とアルゴリズムⅠ 
数理計画法 
情報科学序説 
機械学習 
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Memberships of academic societies
Institute of Electronics, Information and Communication Engineers 
Association for Natural Language Processing 
Japanese Society for Artificial Intelligence 
情報処理学会 
IEEE  1999/05/01-Present 
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Open lecture
模擬授業「自然から学ぶアルゴリズム-ナチュラル・コンピューティング-」  Others  2015/07-2015/07  自然界には,多くの有益なアイデアが存在しています.例えば,生物は長い年月をかけて進化し,環境に適応しています.また,単純な生物でも群としては驚くほど知的な振る舞いをします.このような現象をコンピュータ上に実現し,情報処理に応用する研究であるナチュラルコンピューティングを紹介します. 
模擬授業「自然から学ぶアルゴリズム-ナチュラル・コンピューティング-」  Others  2009/11-2009/11  自然界には,多くの有益なアイデアが存在しています.例えば,生物は長い年月をかけて進化し,環境に適応しています.また,単純な生物でも群としては驚くほど知的な振る舞いをします.このような現象をコンピュータ上に実現し,情報処理に応用する研究であるナチュラルコンピューティングを紹介します. 
模擬授業「人工知能」  Open lecture  2008/10-2008/10  人工知能は,知的活動が可能な知的機械(コンピュータ)の実現を目指す研究分野です.推論,探索などの基礎分野から音声・画像認識,自然言語理解などの応用分野まで,人間の知的活動の一部を実現するために様々な研究が行われています.本講義では,ゲーム木探索を取り上げ,オセロゲームや将棋のようなゲームにおいて,指し手をコンピュータで計算する方法について,基本的な考え方を紹介します. 
平成17年度広島市立大学情報科学部公開講座  Open lecture  2005/11-2005/11  自然から学ぶアルゴリズム -ナチュラル・コンピューティング- 
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