S. Sakai

发表

Solving Constrained Optimization Problems by the ε Constrained Particle Swarm Optimizer with Adaptive Velocity Limit Control

T. Takahama, S. Sakai, 2006, 2006 IEEE Conference on Cybernetics and Intelligent Systems.

Constrained Optimization by ε Constrained Differential Evolution with Dynamic ε-Level Control

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2008 .

Efficient Constrained Optimization by the ε Constrained Rank-Based Differential Evolution

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2012, 2012 IEEE Congress on Evolutionary Computation.

Efficient Constrained Optimization by the \varepsilon Constrained Differential Evolution with Rough Approximation

T. Takahama, S. Sakai, 2015 .

Efficient Optimization by Differential Evolution using Rough Approximation Model with Adaptive Control of Error Margin

T. Takahama, S. Sakai, 2008 .

Reducing Function Evaluations Using Adaptively Controlled Differential Evolution with Rough Approximation Model

T. Takahama, S. Sakai, 2010 .

Learning fuzzy control rules by a constrained Powell's method

T. Takahama, S. Sakai, 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

Large scale optimization by differential evolution with landscape modality detection and a diversity archive

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2012, 2012 IEEE Congress on Evolutionary Computation.

Adaptive Directional Mutation for an Adaptive Differential Evolution Algorithm

T. Takahama, S. Sakai, 2020, 2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS).

An adaptive differential evolution with exploitation and exploration by extreme individuals

T. Takahama, S. Sakai, 2017, 2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).

Selecting strategies in particle swarm optimization by sampling-based landscape modality detection using inner products

T. Takahama, S. Sakai, 2014, 2014 Proceedings of the SICE Annual Conference (SICE).

Reducing the Number of Function Evaluations in Differential Evolution by Estimated Comparison Method Using an Approximation Model with Low Accuracy

T. Takahama, S. Sakai, Akira Hara, 2008 .

Improving an adaptive differential evolution using hill-valley detection

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2016, Int. J. Hybrid Intell. Syst..

An optimization algorithm "Team Model"

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

Efficient constrained optimization by the ε constrained differential evolution with rough approximation using kernel regression

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2013, 2013 IEEE Congress on Evolutionary Computation.

A comparative study on kernel smoothers in Differential Evolution with estimated comparison method for reducing function evaluations

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2009, 2009 IEEE Congress on Evolutionary Computation.

Constrained Optimization by epsilon Constrained Particle Swarm Optimizer with epsilon-level Control

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2005, WSTST.

Solving Nonlinear Constrained Optimization Problems by the ε Constrained Differential Evolution

Tetsuyuki Takahama, Setsuko Sakai, Noriyuki Iwane, 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

Constrained Optimization by the epsilon Constrained Hybrid Algorithm of Particle Swarm Optimization and Genetic Algorithm

Tetsuyuki Takahama, Setsuko Sakai, Noriyuki Iwane, 2005, Australian Conference on Artificial Intelligence.

Constrained optimization by the ε constrained differential evolution with an archive and gradient-based mutation

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2010, IEEE Congress on Evolutionary Computation.

Solving Difficult Constrained Optimization Problems by the ε Constrained Differential Evolution with Gradient-Based Mutation

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2009 .

Constrained Optimization by the ε Constrained Differential Evolution with Gradient-Based Mutation and Feasible Elites

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Constrained optimization by applying the /spl alpha/ constrained method to the nonlinear simplex method with mutations

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2005, IEEE Transactions on Evolutionary Computation.

Constrained Optimization by α Constrained Genetic Algorithm (αGA)

T. Takahama, S. Sakai, 2003 .

Constrained optimization by improved particle swarm optimization with the equivalent penalty coefficient method

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2020, Artificial Life and Robotics.

An Equivalent Penalty Coefficient Method: An Adaptive Penalty Approach for Population-Based Constrained Optimization

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2019, 2019 IEEE Congress on Evolutionary Computation (CEC).

Efficient constrained optimization by the ε constrained adaptive differential evolution

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2010, IEEE Congress on Evolutionary Computation.

Efficient nonlinear optimization by differential evolution with a rotation-invariant local sampling operation

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

Solving nonlinear optimization problems by Differential Evolution with a rotation-invariant crossover operation using Gram-Schmidt process

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2010, 2010 Second World Congress on Nature and Biologically Inspired Computing (NaBIC).

Efficient Constrained Optimization by the ε Constrained Differential Evolution Using an Approximation Model with Low Accuracy

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2009 .

Reducing function evaluations in Differential Evolution using rough approximation-based comparison

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

Learning Fuzzy Rules for Bang-Bang Control by Reinforcement Learning Method

Tetsuyuki Takahama, Setsuko Sakai, Hisakazu Ogura, 1996 .

Constrained optimization by constrained genetic algorithm (alpha GA)

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2004, Systems and Computers in Japan.

Learning fuzzy control rules by vector simplex method

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

Tuning fuzzy control rules by the ? constrained method which solves constrained nonlinear optimization problems

Tetsuyuki Takahama, Setsuko Sakai, T. Takahama, 2000 .

Particle swarm optimization with mutation operations controlled by landscape modality estimation using hill-valley detection

Tetsuyuki Takahama, Setsuko Sakai, Akira Hara, 2016, Artificial Life and Robotics.

The velocity updating rule according to an oblique coordinate system with mutation and dynamic scaling for particle swarm optimization

T. Takahama, S. Sakai, 2018, Artificial Life and Robotics.

Structural learning of neural networks by differential evolution with degeneration using mappings

Tetsuyuki Takahama, Setsuko Sakai, Akira Hara, 2007, 2007 IEEE Congress on Evolutionary Computation.