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Kyoto University  Graduate School, Division of Engineering  電気工学第二専攻  Doctor course  1987  Withdrawn after completion of required course credits 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  The Velocity Updating Rule According to an Oblique Coordinate System with Mutation and Dynamic Scaling for Particle Swarm Optimization  T.Takahama, S.Sakai  Artificial Life and Robotics  23/ 4, 618-627  2018/12  Particle swarm optimization (PSO) has been showing powerful search performance especially in separable and unimodal problems. However, the performance is deteriorated in non-separable problems such as rotated problems. In this study, a new velocity updating rule according to an oblique coordinate system, instead of an orthogonal coordinate system, is proposed to solve non-separable problems. Two mutation operations for the best particle and the worst particle are proposed to improve the diversity of particles and to decrease the degradation of moving speed of particles. Also, the vectors generated according to the oblique coordinate system is dynamically scaled in order to improve the robustness and efficiency of the search. The advantage of the proposed method is shown by solving various problems including separable, non-separable, unimodal, and multimodal problems, and their rotated problems and by comparing the results of the proposed method with those of standard PSO. 
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 (international conference proceedings)  Joint  Particle Swarm Optimization with the Velocity Updating Rule According to an Oblique Coordinate System  Tetsuyuki Takahama and Setsuko Sakai  Proc. of the 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM2017)  70-77  2017/10  Optimization problems have some characteristics: Dependency among decision variables such as separable or non-separable problems, and landscape modality such as unimodal or multimodal problems. Particle swarm optimization (PSO) has been shown powerful search performance especially in separable and unimodal problems. However, the performance is deteriorated in non-separable problems such as rotated problems. Although velocity updating rules using random rotation matrices have been proposed to solve non-separable problems, the computational cost of generating the random rotation matrices is very high. In this study, a new velocity updating rule according to an oblique coordinate system, instead of an orthogonal coordinate system, is proposed to solve non-separable problems. Also, two mutation operations for the worst particle and the best particle are proposed to improve the diversity and the convergence of particles, respectively. The advantage of the proposed method is shown by solving various problems including unimodal problems, multimodal problems, and rotated problems and by comparing the results of the proposed method with those of standard PSO. 
Research paper (bulletin of university, research institution)  Joint  適応型差分進化JADEにおける個体順位に基づくグループ別パラメータ制御  阪井節子,高濱徹行  数理解析研究所講究録2044  159-170  2017/09 
Research paper (international conference proceedings)  Joint  An Adaptive Differential Evolution with Exploitation and Exploration by Extreme Individuals  Tetsuyuki Takahama and Setsuko Sakai  Proc. of SICE Annual Conference 2017 (SICE2017)  1147-1152  2017/09  In a natural population, extreme individuals are very important for survival of the population. When the main population is destroyed by catastrophes, the few extreme individuals gain significance and will insure the survival of the population. Differential Evolution (DE) has been successfully applied to various optimization problems. However, DE sometimes trapped into some local solutions, which is a kind of a catastrophe. In this study, the extreme individuals are paid attention to. The best individuals perform exploitation or local search to keep extremely good positions. The worst individuals perform exploration or global search to keep positions far from the best individuals. Other individuals perform adaptive search based on JADE which is one of the most successful algorithms on controlling algorithm parameters. In JADE, the values of two algorithm parameters are generated according to two probability density functions which are learned by the values in success cases where the child is better than the parent. The advantage of JADE with exploitation and exploration by extreme individuals is shown by solving thirteen benchmark problems. 
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Research presentations
Oral presentation(general)  差分進化における相関係数に基づく遺伝子のグループ化とグループ単位の交叉の提案  情報処理学会 第120回数理モデル化と問題解決研究会  2018/09/26  最適化が困難な変数間依存性の強い問題に出現する特徴的な分布として,細い楕円形状の分布がある.このような場合に優れた子個体を生成するには,楕円形状の長軸に沿って変数を同時に変更する必要がある.また,同様の分布は,変数分離型の問題において探索点集合が最適解から離れている場合にも出現する.差分進化における2項交叉は,各変数(遺伝子) について同じ確率で交叉を行うかどうかを決定しているため,特定の遺伝子を同時に交叉することは困難である.本研究では,このような形状を検出するために探索点の相関係数を利用する方法を提案する.探索点の分布から相関行列を求め,相関の強い遺伝子をグループ化し,グループ単位で遺伝子を同時に交叉する(あるいは,交叉しない).本手法を差分進化の代表的手法であるJADE に導入し,幾つかのベンチマーク問題を最適化し,性能を比較することにより,本手法の効果を調べる. 
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 
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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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