Educe University Faculty Information

Present specialized field
Academic background
Research activities
Business career
Book and thesis
Subject
Developed teaching materials, textbooks, reference books

（Last updated : 2025-04-01 12:09:23）

TAKAHAMA Setsuko
Hiroshima shudo University The Faculty of Commercial Sciences

Professor

■ Present specialized field

●Specialized field
Other, Other
●Keyword
●The main research themes
●Capable of joint research and research consultation content

■ Academic background

1.	1981/04～1986/03	Osaka University Graduate School, Division of Engineering Science 〔Doctoral course〕 Accomplished credits for doctoral program
2.	1987/04 Degree Acquisition	Osaka University Doctor of Engineering

■ Research activities

1.	1981～	The Operations Research Society of Japan
2.	1990～	Japan Society for Fuzzy Theory and intelligent informatics
3.	1998～	The Japan Society for Production Management (JSPM)
4.	～	The Japanese Society for Evolutionary Computation

■ Business career

1.	1998/04～1999/03	Hiroshima shudo University The Faculty of Commercial Sciences Professor
2.	1999/04～2001/03	Hiroshima shudo University Professor
3.	2001/04～	Hiroshima shudo University The Faculty of Commercial Sciences Professor

■ Book and thesis

1.	Book	Improving Speciation-Based Particle Swarm Optimization with Graphs by Sphere Mutation, Local Mutation, and Parameter Adjustment for Multimodal Optimization (Collaboration) 2025/03
2.	Book	A Study on Crossover Operations Using Hill-Valley Detection for Multimodal Optimization by Particle Swarm Optimization with Graph-Based Speciation (Collaboration) 2024/02
3.	Book	A Study on Converging and Moving Detection Using Distance Between the Center and the Best Solution for Particle Swarm Optimization (Collaboration) 2023/02
4.	Book	A Study on Multi-Armed Bandit Algorithms for Dynamic Selection of Parameters and Topologies in Particle Swarm Optimization (Collaboration) 2022/02
5.	Thesis	Improving a Real-Coded Genetic Algorithm Using an Outward Vector Rate and Pallelotope-Shaped Crossover (Collaboration) 2023/01
6.	Thesis	Converging and Moving Detection Using an Outward Vector Rate for Adaptive Differential Evolution (Collaboration) 2022/11
7.	Thesis	Multimodal Optimization by Particle Swarm Optimization with Graph-Based Speciation Using β-Relaxed Relative Neighborhood Graph and Seed-Centered Mutation (Collaboration) 2022/03
8.	Thesis	An Adaptive Differential Evolution Algorithm Utilizing Failure Information and Success Information (Collaboration) 2021/06
9.	Thesis	Multimodal Optimization by Particle Swarm Optimization with Graph-Based Speciation Using β-Relaxed Relative Neighborhood Graph (Collaboration) 2021/06
10.	Thesis	Adaptive Directional Mutation for an Adaptive Differential Evolution Algorithm (Collaboration) 2020/12
11.	Thesis	A Correlation-Based Group-Wise Crossover Operation Based on Gene Grouping using Correlation Coeﬃcients for an Adaptive Diﬀerential Evolution Algorithm (Collaboration) 2020/06
12.	Thesis	An Equivalent Penalty Coefficient Method: An Adaptive Penalty Approach for Population-Based Constrained Optimization (Collaboration) 2019/06
13.	Thesis	Particle Swarm Optimization with the Velocity Updating Rule According to an Oblique Coordinate System (Collaboration) 2017/10
14.	Thesis	An Adaptive Differential Evolution with Exploitation and Exploration by Extreme Individuals (Collaboration) 2017/09
15.	Thesis	An Adaptive Differential Evolution with Learning Parameters According to Groups Defined by the Rank of Objective Values (Collaboration) 2017/07
16.	Thesis	Improving an Adaptive Differential Evolution using Hill-Valley Detection (Collaboration) 2015/11
17.	Thesis	Constrained Optimization by the εConstrained Differential Evolution with an Archive and Gradient-Based Mutation (Collaboration) 2010/07
18.	Thesis	Efficient Constrained Optimization by the Epsilon Constrained Adaptive Differential Evolution (Collaboration) 2010/07
19.	Thesis	Predicting Stock Price Using Neural Networks Optimized by Differential Evolution with Degeneration (Collaboration) 2009/12
20.	Thesis	A Comparative Study on Kernel Smoothers in Differential Evolution with Estimated Comparison Method for Reducing Function Evaluations (Collaboration) 2009/05
21.	Thesis	Fast and Stable Constrained Optimizationby the ε Constrained Differential Evolution (Collaboration) 2009/05
22.	Thesis	Efficient Optimization by Differential Evolution using Rough Approximation Model with Adaptive Control of Error Margin (Collaboration) 2008/09
23.	Thesis	Reducing Function Evaluations in Differential Evolution using Rough Approximation-Based Comparison (Collaboration) 2008/06
24.	Thesis	Reducing the Number of Function Evaluations in Differential Evokutuion by Estimated Comparison Method Using an Approximation Model with Low Accuracy (Collaboration) 2008/05
25.	Thesis	Structural Learningof Neural Networks by Differential Evolution with Degeneration using Mappings (Collaboration) 2007/09
26.	Thesis	Solving Nonlinear Constrained Optimization Problems by the Epsilon Constrained Differential Evolution (Collaboration) 2006/10
27.	Thesis	Constrained Optimization by the ε Constrained Differential Evolution with Gradient-Based Mutation and Feasible Elites (Collaboration) 2006/07
28.	Thesis	Constrained Optimization by the Epsilon Constrained Genetic Algorithm (Collaboration) 2006/06
29.	Thesis	Solving Constrained Optimization Problems by the Epsilon Constrained Particle Swarm Optimizer with Adaptive Velocity Limit Control (Collaboration) 2006/06
30.	Thesis	Constrained Optimization by the Epsilon Constrained Hybrid Algorithm of Particle Swarm Optimization and Genetic Algorithm (Collaboration) 2005/12
31.	Thesis	Constrained Optimization by Applying the α Constrained Method to the Nonlinear Simplex Method with Mutations (Collaboration) 2005/10
32.	Thesis	Constrained Optimization by Epsilon Constrained Particle Swarm Optimizer with Epsilon-level Control (Collaboration) 2005/05
33.	Thesis	Constrained Optimization by the α Constrained Particle Swarm Optimizer (Collaboration) 2005/05
34.	Thesis	Structural Learning of Neural Networks by Coevolutionary Genetic Algorithm with Degeneration (Collaboration) 2004/10
35.	Thesis	Constrained Optimization by Combining the α Constrained Method with Particle Swarm Optimization (Collaboration) 2004/09
36.	Thesis	Constrained Optimization by Alpha Constrained Genetic Algorithm (alphaGA) (Collaboration) 2004/05
37.	Thesis	tructural Optimization by Genetic Algorithm with Degeneration (GA^d) (Collaboration) 2004/05
38.	Thesis	A Study on Adaptive Control of Degeneration Speed in Structural Learning of Fuzzy Rules by Genetic Algorithms with Degeneration GA^d (Collaboration) 2004/02
39.	Thesis	Structural Learning of RBF-Fuzzy Rule Bases Based on Information Criteria and Degeneration (Collaboration) 2003/10
40.	Thesis	Constrained Optimization by Alpha Constrained Genetic Algorithm (alphaGA) (Collaboration) 2003/04
41.	Thesis	Learning Structure of RBF-Fuzzy Rule Bases by Degeneration (Collaboration) 2003/03
42.	Thesis	Structural Optimization by Genetic Algorithm with Degeneration (GA^d) (Collaboration) 2003/03
43.	Thesis	Structural Optimization of Neural Network by Genetic Algorithm with Damaged Genes (Collaboration) 2002/11
44.	Thesis	Structural Learning by Genetic Algorithm with Damaged Genes (Collaboration) 2002/09
45.	Thesis	Learning Game Strategy in an Artificial Game Society (Collaboration) 2002/03
46.	Thesis	Interactive Learning of Multiobjective Fuzzy Control Rules by Multiobjective Nonlinear Optimization Method "Vector Simplex" (Collaboration) 2001/11
47.	Thesis	MGGA: Genetic Algorithm with Mutant Genes (Collaboration) 2001/09
48.	Thesis	Learning Game Strategy by Multi-Agent TD Players (Collaboration) 2001/08
49.	Thesis	Learning Fuzzy Control Rules by Vector Simplex Method (Collaboration) 2001/07
50.	Thesis	Team Model and Taught-by-the-best Operation (Collaboration) 2001/05
51.	Thesis	Multiobjective Nonlinear Optimization Method "Vector Simplex" (Collaboration) 2000/12
52.	Thesis	Learning Fuzzy Inference Rules with Shape Parameters (Collaboration) 2000/09
53.	Thesis	Tuning Fuzzy Control Rules by the α Constrained Method which Solves Constrained Nonlinear Optimization Problems (Collaboration) 2000/09
54.	Thesis	Learning Fuzzy Control Rules by Alpha Constrained Simplex Method (Collaboration) 2000/07
55.	Thesis	Team Model which Solves Optimization Problems Based on Teaching by Teams (Collaboration) 2000/01
56.	Thesis	An Optimization Algorithm ``Team Model'' (Collaboration) 1999/10
57.	Thesis	Learning fuzzy control rules by alpha constrained simplex method (Collaboration) 1999/08
58.	Thesis	Learning Fuzzy Control Rules by α Constrained Powell's Method (Collaboration) 1999/08
59.	Thesis	Tunning Fuzzy Control Rules by Alpha Constrained Method which Solves Constrained Nonlinear Optimization Problems (Collaboration) 1999/05
60.	Thesis	Learning Rules for Fuzzy Scaling Control by Genetic Algorithms (Collaboration) 1998/01
61.	Thesis	A Method of Separating the Graphical User Interface in CAI System (Collaboration) 1997/01
62.	Thesis	Learning Fuzzy Rules for Bang-Bang Control by Reinforcement Learning Method (Collaboration) 1996/04
63.	Thesis	Learning Fuzzy Rules for Bang-Bang Control by Reinforcement Learning Method (Collaboration) 1996/02
64.	Thesis	The Possibility Distribution of α-optimal Value Z(α) in Fuzzy Linear Programming Problem (Collaboration) 1994/05
65.	Thesis	A Model for Real Poker with the Upper Bound of Asset (Single) 1986/07
66.	Thesis	Solutions to Three-Person Hi-Lo Poker (Single) 1984/05
67.	Thesis	Solutions to a Class of Two-Person Hi-Lo Poker (Collaboration) 1982/01
68.	Thesis	Partial Information in a Simplified Two-Person Poker (Collaboration) 1981/12
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■ Subject

1.	Data Processing
2.	Data Processing
3.	Directed Individual Studies
4.	Directed Individual Studies
5.	Directed Individual Studies
6.	Directed Research
7.	Management and Information Sciences I
8.	Management and Information Sciences II
9.	Special Lecture B2a(Exercise in Algorithm and Programming I)
10.	Special Lecture B2a(Exercise in Algorithm and Programming II)
11.	Studies in Information Management of Business Administration I
12.	Studies in Information Management of Business Administration II
13.	Studies in Information Managemnt of Business Administration
14.	Thesis
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■ Developed teaching materials, textbooks, reference books

1.	2020/07 Contribution Type : 単著
2.	2020/07 Contribution Type : 単著
3.	2020/07 Contribution Type : 単著
4.	2020/07 Contribution Type : 単著
5.	2021/01 Contribution Type : 単著
6.	2021/01 Contribution Type : 単著
7.	2021/01 Contribution Type : 単著
8.	2021/01 Contribution Type : 単著
9.	2021/01 Contribution Type : 単著
10.	2021/07 Contribution Type : 単著
11.	2021/07 Contribution Type : 単著
12.	2021/07 Contribution Type : 単著
13.	2021/07 Contribution Type : 単著
14.	2022/01 Contribution Type : 単著
15.	2022/01 Contribution Type : 単著
16.	2022/01 Contribution Type : 単著
17.	2022/01 Contribution Type : 単著
18.	2023/07 Contribution Type : 単著
19.	2023/07 Contribution Type : 単著
20.	2023/07 Contribution Type : 単著
21.	2024/01 Contribution Type : 単著
22.	2024/01 Contribution Type : 単著
23.	2024/04 Contribution Type : 単著
24.	2024/09 Contribution Type : 単著
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