Google Scholar Citations

Journal Papers

  1. Pramudita Satria Palar, Rafael Stevenson, Muhammad Ridho Al Hafiz, Mohammad Daffa Robani, Koji Shimoyama, and Lavi Rizki Zuhal, “Global Sensitivity Analysis of Stochastic Re-entry Trajectory using Explainable Surrogate Models,” Acta Astronautica, Vol. 222, September 2024, pp. 109–125.
    DOI: 10.1016/j.actaastro.2024.05.042
  2. Pramudita Satria Palar, Yohanes Bimo Dwianto, Lavi Rizki Zuhal, Joseph Morlier, Koji Shimoyama, and Shigeru Obayashi, “Multi-Objective Design Space Exploration using Explainable Surrogate Models,” Structural and Multidisciplinary Optimization, Vol. 67, February 2024, Article No. 38.
    DOI: 10.1007/s00158-024-03769-z
  3. Pradeep Mohanasundaram, Koji Shimoyama, Frédéric Gillot, and Sébastien Besset, “Modelling Friction-Induced Dynamic Instability Dedicated for Isogeometric Formulation,” Shock and Vibration, Vol. 2023, November 2023, Article ID 8669237.
    DOI: 10.1155/2023/8669237
  4. Pramudita Satria Palar, Lavi Rizki Zuhal, and Koji Shimoyama, “Global Sensitivity Analysis in Aerodynamic Design using Shapley Effects and Polynomial Chaos Regression,” IEEE Access, Vol. 11, October 2023, pp. 114825–114839.
    DOI: 10.1109/ACCESS.2023.3324918
  5. Hisashi Nakamura, Juwei Zhang, Kaito Hirose, Koji Shimoyama, Takamasa Ito, and Tralin Kanaumi, “Generating Simplified Ammonia Reaction Model using Genetic Algorithm and its Integration into Numerical Combustion Simulation of 1 MW Test Facility,” Applications in Energy and Combustion Science, Vol. 15, September 2023, 100187232.
    DOI: 10.1016/j.jaecs.2023.100187
  6. Pramudita Satria Palar, Lavi Rizki Zuhal, and Koji Shimoyama, “Enhancing the Explainability of Regression-based Polynomial Chaos Expansion by Shapley Additive Explanations,” Reliability Engineering and System Safety, Vol. 232, April 2023, 109045.
    DOI: 10.1016/j.ress.2022.109045
  7. Pramudita Satria Palar, Lucia Parussini, Luigi Bregant, Koji Shimoyama, and Lavi Rizki Zuhal, “On Kernel Functions for Bi-Fidelity Gaussian Process Regressions,” Structural and Multidisciplinary Optimization, Vol. 66, February 2023, Article No. 37.
    DOI: 10.1007/s00158-023-03487-y
  8. Akbar Mohammadi-Ahmar, Arash Mohammadi, Mehrdad Raisee, and Koji Shimoyama, “Model Order Reduction for Film Cooled Applications under Probabilistic Conditions: Sparse Reconstruction of POD in Combination with Kriging,” Structural and Multidisciplinary Optimization, Vol. 65, September 2022, Article No. 283.
    DOI: 10.1007/s00158-022-03384-w
  9. Timothy M. S. Jim, Ghifari A. Faza, Pramudita S. Palar, and Koji Shimoyama, “A Multiobjective Surrogate-Assisted Optimisation and Exploration of Low-Boom Supersonic Transport Planforms,” Aerospace Science and Technology, Vol. 128, September 2022, Article 107747.
    DOI: 10.1016/j.ast.2022.107747
  10. Koji Shimoyama and Atsuki Komiya, “Multi-Objective Bayesian Topology Optimization of a Lattice-Structured Heat Sink in Natural Convection,” Structural and Multidisciplinary Optimization, Vol. 65, January 2022, Article No. 1.
    DOI: 10.1007/s00158-021-03092-x
  11. Potsawat Boonjaipetch, Koji Shimoyama, and Shigeru Obayashi, “Parametric Study on Waverider Configurations at Low-supersonic Speed for Low-boom Supersonic Transport,” Transactions of the Japan Society for Aeronautical and Space Sciences, Vol. 64, No. 6, November 2021, pp. 325–334.
    DOI: 10.2322/tjsass.64.325
  12. Timothy M. S. Jim, Ghifari A. Faza, Pramudita S. Palar, and Koji Shimoyama, “Bayesian Optimization of a Low-Boom Supersonic Wing Planform,” AIAA Journal, Vol. 59, No. 11, November 2021, pp. 4514–4529.
    DOI: 10.2514/1.J060225
  13. Pradeep Mohanasundaram, Frédéric Gillot, Sébastien Besset, and Koji Shimoyama, “Multi-References Acquisition Strategy for Shape Optimization of Disc-Pad Like Mechanical Systems,” Structural and Multidisciplinary Optimization, Vol. 64, Issue 4, October 2021, pp. 1863–1885.
    DOI: 10.1007/s00158-021-02947-7
  14. Lavi R. Zuhal, Kemas Zakaria, Pramudita Satria Palar, Koji Shimoyama, and Rhea Patricia Liem, “Polynomial Chaos-Kriging with Gradient Information for Surrogate Modeling in Aerodynamic Design,” AIAA Journal, Vol. 59, No. 8, August 2021, pp. 2950–2967.
    DOI: 10.2514/1.J059905
  15. Arash Mohammadi, Koji Shimoyama, Mohammad Sadeq Karimi, and Mehrdad Raisee, “Efficient Uncertainty Quantification of CFD Problems by Combination of Proper Orthogonal Decomposition and Compressed Sensing,” Applied Mathematical Modelling, Vol. 94, June 2021, pp. 187–225.
    DOI: 10.1016/j.apm.2021.01.012
  16. Yuki Sano, Yuji Akai, Takumi Takahashi, Keisuke Ishii, Kichinosuke Fukuhara, Takeo Kobayashi, and Koji Shimoyama, “Verification Method to Optimize Multiple Functions of Valve Train in a Short Time Using Multi-objective Design Exploration,”Transactions of Society of Automotive Engineers of Japan, Vol. 52, No. 1, January 2021, pp. 13–18 (in Japanese).
    DOI: 10.11351/jsaeronbun.52.13
  17. Koji Shimoyama, Yoshio Sato, Jun Onodera, and Jun Liu, “Measurement-based Strategies for High-Fidelity Thermo-Fluid Dynamics Simulation of an Automotive Heat Exchanger,” Journal of Fluid Science and Technology, Vol. 16, Issue 1, January 2021, pp. JFST0006.
    DOI: 10.1299/jfst.2021jfst0006
  18. Yi Xiang, Koji Shimoyama, Keiichi Shirasu, and Go Yamamoto, “Machine Learning-Assisted High-Throughput Molecular Dynamics Simulation of High-Mechanical Performance Carbon Nanotube Structure,” Nanomaterials, Vol. 10, Issue 12, December 2020, Article No. 2459.
    DOI: 10.3390/nano10122459
  19. Tadateru Ishide, Yasuaki Takagi, Sakachi Otsubo, Koji Shimoyama, and Shigeru Obayashi, “Aerodynamic Improvement of a Delta Wing by Using Combination of Leading Edge Flaps,” Journal of the Japanese Society for Experimental Mechanics,Vol. 20, No. 2, June 2020, pp. 101–108 (in Japanese).
    DOI: 10.11395/jjsem.20.101
  20. Pramudita Satria Palar, Lavi Rizki Zuhal, and Koji Shimoyama, “Gaussian Process Surrogate Model with Composite Kernel Learning for Engineering Design,” AIAA Journal, Vol. 58, No. 4, April 2020, pp. 1864–1880.
    DOI: 10.2514/1.J058807
  21. Pradeep Mohanasundaram, Frédéric Gillot, Koji Shimoyama, and Sébastien Besset, “Shape Optimization of a Disc-Pad System under Squeal Noise Criteria,” SN Applied Sciences, Vol. 2, Issue 4, April 2020, Article No. 547.
    DOI: 10.1007/s42452-020-2175-8
  22. Yuya Yamaguchi, Daisuke Sasaki, Masato Okamoto, Koji Shimoyama, and Shigeru Obayashi, “Numerical Investigation of Geometrical Corrugation Influence to Vortex Flowfields at Low Reynolds Number,” Journal of Fluid Science and Technology, Vol. 14, No. 3, December 2019, pp. JFST0018.
    DOI: 10.1299/jfst.2019jfst0018
  23. Tomohiro Hirano, Mitsuo Yoshimura, Koji Shimoyama, and Atsuki Komiya, “Thermo-Fluid Dynamic Design Optimization of a Concentric Tube Heat Exchanger,” Journal of Fluid Science and Technology, Vol. 14, No. 2, November 2019, pp. JFST0011.
    DOI: 10.1299/jfst.2019jfst0011
  24. Masaru Kamada, Koji Shimoyama, Fumito Sato, Junya Washiashi, and Yasufumi Konishi, “Multi-Objective Design Optimization of a High Efficiency and Low Noise Blower Unit of a Car Air-Conditioner,” Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Vol. 233, Issue 13, November 2019, pp. 3493–3503.
    DOI: 10.1177/0954407019827131
  25. Lavi Rizki Zuhal, Pramudita Satria Palar, and Koji Shimoyama, “A Comparative Study of Multi-Objective Expected Improvement for Aerodynamic Design,” Aerospace Science and Technology, Vol. 91, August 2019, pp. 548–560.
    DOI: 10.1016/j.ast.2019.05.044
  26. Gota Kikugawa, Yuta Nishimura, Koji Shimoyama, Taku Ohara, Tomonaga Okabe, and Fumio S. Ohuchi, “Data Analysis of Multi-Dimensional Thermophysical Properties of Liquid Substances Based on Clustering Approach of Machine Learning,” Chemical Physics Letters, Vol. 728, August 2019, pp. 109–114.
    DOI: 10.1016/j.cplett.2019.04.075
  27. Nobuo Namura, Koji Shimoyama, Shigeru Obayashi, Yasushi Ito, Shunsuke Koike, and Kazuyuki Nakakita, “Multipoint Design Optimization of Vortex Generators on Transonic Swept Wings,” Journal of Aircraft, Vol. 56, No. 4, July–August 2019, pp. 1291–1302.
    DOI: 10.2514/1.C035148
  28. Koji Shimoyama and Soshi Kawai, “A Kriging-Based Dynamic Adaptive Sampling Method for Uncertainty Quantification,” Transactions of the Japan Society for Aeronautical and Space Sciences, Vol. 62, Issue 3, May 2019, pp. 137–150.
    DOI: 10.2322/tjsass.62.137
  29. Mitsuo Yoshimura, Koji Shimoyama, Takashi Misaka, and Shigeru Obayashi, “Optimization of Passive Grooved Micromixers Based on Genetic Algorithm and Graph Theory,” Microfluidics and Nanofluidics, Vol. 23, Issue 3, March 2019, Article 30.
    DOI: 10.1007/s10404-019-2201-6
  30. Pramudita Satria Palar and Koji Shimoyama, “Efficient Global Optimization with Ensemble and Selection of Kernel Functions For Engineering Design,” Structural and Multidisciplinary Optimization, Vol. 59, Issue 1, January 2019, pp. 93–116.
    DOI: 10.1007/s00158-018-2053-9
  31. Narendra Kurnia Putra, Pramudita Satria Palar, Hitomi Anzai, Koji Shimoyama, and Makoto Ohta, “Multiobjective Design Optimization of Stent Geometry with Wall Deformation for Triangular and Rectangular Struts,” Medical & Biological Engineering & Computing, Vol. 57, Issue 1, January 2019, pp. 15–26.
    DOI: 10.1007/s11517-018-1864-6
  32. Wataru Yamazaki, Tatsuya Kato, Tsubasa Homma, Koji Shimoyama, and Shigeru Obayashi, “Stochastic Tsunami Inundation Flow Simulation via Polynomial Chaos Approach,” Journal of Fluid Science and Technology, Vol. 13, No. 4, November 2018, pp. JFST0025.
    DOI: 10.1299/jfst.2018jfst0025
  33. Pramudita Satria Palar and Koji Shimoyama, “On Efficient Global Optimization via Universal Kriging Surrogate Models,” Structural and Multidisciplinary Optimization, Vol. 57, Issue 6, June 2018, pp. 2377–2397.
    DOI: 10.1007/s00158-017-1867-1
  34. Masashi Tomita, Koji Shimoyama, Yukiko Ehara, So Yamada, and Takashi Kokuryo, “Rule Extraction of Home-Energy Devices in a Smart Home System,” Transactions of the JSME, Vol. 84, No. 859, March 2018, pp. 17-00390 (in Japanese).
    DOI: 10.1299/transjsme.17-00390
  35. Pramudita Satria Palar, Lavi Rizki Zuhal, Koji Shimoyama, and Takeshi Tsuchiya, “Global Sensitivity Analysis via Multi-Fidelity Polynomial Chaos Expansion,” Reliability Engineering and System Safety, Vol. 170, February 2018, pp. 175–190.
    DOI: 10.1016/j.ress.2017.10.013
  36. Nobuo Namura, Koji Shimoyama, and Shigeru Obayashi, “Expected Improvement of Penalty-based Boundary Intersection for Expensive Multiobjective Optimization,” IEEE Transactions on Evolutionary Computation, Vol. 21, No. 6, December 2017, pp. 898–913.
    DOI: 10.1109/TEVC.2017.2693320
  37. Koji Shimoyama and Taiga Kato, “An Evolutionary Constrained Multi-Objective Optimization Algorithm with Parallel Evaluation Strategy,” Journal of Advanced Mechanical Design, Systems, and Manufacturing, Vol. 11, No. 5, October 2017, pp. JAMDSM0051.
    DOI: 10.1299/jamdsm.2017jamdsm0051
  38. Koji Shimoyama and Kazumasa Kamisori, “Study of Aerodynamic and Heat-Exhaust Characteristics for a High-Altitude Long-Endurance Unmanned-Aerial-Vehicle Airfoil,” Journal of Aircraft, Vol. 54, No. 4, July–August 2017, pp. 1317–1327.
    DOI: 10.2514/1.C033978
  39. Nobuo Namura, Koji Shimoyama, and Shigeru Obayashi, “Kriging Surrogate Model with Coordinate Transformation Based on Likelihood and Gradient,” Journal of Global Optimization, Vol. 68, Issue 4, August 2017, pp. 827–849.
    DOI: 10.1007/s10898-017-0516-y
  40. Mitsuo Yoshimura, Koji Shimoyama, Takashi Misaka, and Shigeru Obayashi, “Topology Optimization of Fluid Problems Using Genetic Algorithm Assisted by the Kriging Model,” International Journal for Numerical Methods in Engineering, Vol. 109, Issue 4, January 2017, pp. 514–532.
    DOI: 10.1002/nme.5295
  41. Koji Shimoyama and Akihiro Inoue, “Uncertainty Quantification by the Nonintrusive Polynomial Chaos Expansion with an Adjustment Strategy,” AIAA Journal, Vol. 54, No. 10, October 2016, pp. 3107–3116.
    DOI: 10.2514/1.J054359
  42. Renata Troian, Koji Shimoyama, Frédéric Gillot, and Sébastien Besset, “Methodology for the Design of the Geometry of a Cavity and its Absorption Coefficients as Random Design Variables Under Vibroacoustic Criteria,” Journal of Computational Acoustics, Vol. 24, Issue 2, June 2016, pp. 1650006-1–12.
    DOI: 10.1142/S0218396X16500065
  43. Tadateru Ishide, Shinsuke Seiji, Hiroyuki Ishikawa, Kazuya Naganuma, Sumika Fujimoto, Ryo Fujii, Kazuo Maeno, Koji Shimoyama, and Shigeru Obayashi, “Fluid Force and PIV Measurements around a Flapping Elliptical Wing,” Transactions of the Visualization Society of Japan, Vol. 35, No. 10, October 2015, pp. 37–43 (in Japanese).
    DOI: 10.3154/tvsj.35.37
  44. Chang Luo, Koji Shimoyama, and Shigeru Obayashi, “A Study on Many-Objective Optimization Using the Kriging-Surrogate-Based Evolutionary Algorithm Maximizing Expected Hypervolume Improvement,” Mathematical Problems in Engineering, Vol. 2015, 2015, Article ID 162712.
    DOI: 10.1155/2015/162712
  45. Kazuya Seo, Koji Shimoyama, Ken Ohta, Yuji Ohgi, and Yuji Kimura, “Optimization of Flight Distance and Robustness in the Discus,” Sports Engineering, Vol. 18, Issue 1, March 2015, pp. 55–65.
    DOI: 10.1007/s12283-014-0166-y
  46. Koji Shimoyama, Hiroki Nakanomyo, and Shigeru Obayashi, “Airport Terrain-Induced Turbulence Simulations Integrated with Weather Prediction Data,” Transactions of the Japan Society for Aeronautical and Space Sciences, Vol. 56, No. 5, September 2013, pp. 286–292.
    DOI: 10.2322/tjsass.56.286
  47. Koji Shimoyama, Koma Sato, Shinkyu Jeong, and Shigeru Obayashi, “Updating Kriging Surrogate Models Based on the Hypervolume Indicator in Multi-Objective Optimization,” Journal of Mechanical Design, Transactions of the ASME, Vol. 135, No. 9, September 2013, pp. 094503-1–7.
    DOI: 10.1115/1.4024849
  48. Kazuya Seo and Koji Shimoyama, “The Visualization Concerning the Optimization of Discus – PIV, Smoke Observation, SOM and Animation –,” Journal of the Visualization Society of Japan, Vol. 33, No. 130, July 2013, pp. 92–96 (in Japanese).
    DOI: 10.3154/jvs.33.130_6
  49. Shinkyu Jeong, Daichi Ono, Koji Shimoyama, and Atsushi Hashimoto, “Sonic Boom Analysis under Conditions of Atmospheric Uncertainty Using Polynomial Chaos,” Transactions of the Japan Society for Aeronautical and Space Sciences, Vol. 56, No. 3, May 2013, pp. 129–136.
    DOI: 10.2322/tjsass.56.129
    (“Erratum for Vol. 56, No. 3, page 135: Sonic Boom Analysis under Conditions of Atmospheric Uncertainty Using Polynomial Chaos,” Transactions of the Japan Society for Aeronautical and Space Sciences, Vol. 57, No. 4, June 2014, pp. 245. DOI: 10.2322/tjsass.57.245)
  50. Koji Shimoyama, Shinkyu Jeong, and Shigeru Obayashi, “Comparison of Sample Addition Criteria for Kriging Response Surface Models in Multi-Objective Optimization,” Transaction of the Japanese Society for Evolutionary Computation, Vol. 3, No. 3, December 2012, pp. 173–184 (in Japanese).
    DOI: 10.11394/tjpnsec.3.173
  51. Nobuo Namura, Koji Shimoyama, Shinkyu Jeong, and Shigeru Obayashi, “Kriging/RBF-Hybrid Response Surface Methodology for Highly Nonlinear Functions,” Journal of Computational Science and Technology, Vol. 6, No. 3, July 2012, pp. 81–96.
    DOI: 10.1299/jcst.6.81
  52. Koji Shimoyama, Kazuya Seo, Tsuyoshi Nishiwaki, Shinkyu Jeong, and Shigeru Obayashi, “Design Optimization of a Sport Shoe Sole Structure by Evolutionary Computation and Finite Element Method Analysis,” Proceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology, Vol. 225, No. 4, December 2011, pp. 179–188.
    DOI: 10.1177/1754337111414485
  53. Seiichiro Morizawa, Koji Shimoyama, Shigeru Obayashi, Kenichi Funamoto, and Toshiyuki Hayase, “Implementation of Visual Data Mining for Unsteady Blood Flow Field in an Aortic Aneurysm,” Journal of Visualization, Vol. 14, No. 4, December 2011, pp. 393–398.
    DOI: 10.1007/s12650-011-0101-2
    (“Erratum to: Implementation of Visual Data Mining for Unsteady Blood Flow Field in an Aortic Aneurysm,” Journal of Visualization, Vol. 14, No. 4, December 2011, pp. 399. DOI: 10.1007/s12650-011-0111-0)
  54. Koji Shimoyama, Shu Yoshimizu, Shinkyu Jeong, Shigeru Obayashi, and Yasuyuki Yokono,“Multi-Objective Design Optimization for a Steam Turbine Stator Blade Using LES and GA,” Journal of Computational Science and Technology, Vol. 5, No. 3, November 2011, pp. 134–147.
    DOI: 10.1299/jcst.5.134
  55. Shinkyu Jeong and Koji Shimoyama, “Review of Data Mining for Multi-Disciplinary Design Optimization,” Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, Vol. 225, No. 5, May 2011, pp. 469–479.
    DOI: 10.1177/09544100JAERO906
  56. Shigeru Obayashi, Shinkyu Jeong, Koji Shimoyama, Kazuhisa Chiba, and Hiroyuki Morino, “Multi-Objective Design Exploration and its Applications,” International Journal of Aeronautical and Space Science, Vol. 11, Issue 4, December 2010, pp. 247–265.
    DOI: 10.5139/IJASS.2010.11.4.247
  57. Koji Shimoyama, Kazuyuki Sugimura, Shinkyu Jeong, and Shigeru Obayashi, “Performance Map Construction for a Centrifugal Diffuser with Data Mining Techniques,” Journal of Computational Science and Technology, Vol. 4, No. 1, April 2010, pp. 36–50.
    DOI: 10.1299/jcst.4.36
  58. Shinkyu Jeong, Shoichi Hasegawa, Koji Shimoyama, and Shigeru Obayashi, “Development and Investigation of Efficient GA/PSO-Hybrid Algorithm Applicable to Real-World Design Optimization,” IEEE Computational Intelligence Magazine, Vol. 4, Issue 3, August 2009, pp. 36–44.
    DOI: 10.1109/MCI.2009.933099
  59. Koji Shimoyama, Jin Ne Lim, Shinkyu Jeong, Shigeru Obayashi, and Masataka Koishi, “Practical Implementation of Robust Design Assisted by Response Surface Approximation and Visual Data-Mining,” Journal of Mechanical Design, Transactions of the ASME, Vol. 131, No. 6, June 2009, pp. 061007-1–11.
    DOI: 10.1115/1.3125207
  60. Akira Oyama, Yoshiyuki Okabe, Koji Shimoyama, and Kozo Fujii, “Aerodynamic Multiobjective Design Exploration of a Flapping Airfoil Using a Navier-Stokes Solver,” Journal of Aerospace Computing, Information, and Communication, Vol. 6, No. 3, March 2009, pp. 256–270.
    DOI: 10.2514/1.35992
  61. Koji Shimoyama, Shinkyu Jeong, and Shigeru Obayashi, “Real-World Application of Robust Design Optimization Assisted by Response Surface Approximation and Visual Data-Mining,” Transactions of the Japanese Society for Artificial Intelligence, Vol. 24, No. 1, January 2009, pp. 13–24 (in Japanese).
    DOI: 10.1527/tjsai.24.13
  62. Koji Shimoyama, Akira Oyama, and Kozo Fujii, “Development of Multi-Objective Six-Sigma Approach for Robust Design Optimization,” Journal of Aerospace Computing, Information, and Communication, Vol. 5, No. 8, August 2008, pp. 215–233.
    DOI: 10.2514/1.30310
  63. Akira Oyama, Koji Shimoyama, and Kozo Fujii, “New Constraint-Handling Method for Multi-Objective and Multi-Constraint Evolutionary Optimization,” Transactions of the Japan Society for Aeronautical and Space Sciences, Vol. 50, No. 167, May 2007, pp. 56–62.
    DOI: 10.2322/tjsass.50.56

Books and Book Chapters

  1. Koji Shimoyama and Shigeru Obayashi, “Visual Data Mining in Fluid Dynamics,” Simulation Dictionary, Japan Society for Simulation Technology (Ed.), Corona Publishing Co., Ltd., Tokyo, Japan, 2012, pp. 348 (in Japanese).
    ISBN: 978-4339024586
  2. Koji Shimoyama, Shu Yoshimizu, Shinkyu Jeong, Shigeru Obayashi, and Yasuyuki Yokono, “Multi-Objective Design Optimization for a Steam Turbine Stator Blade Using LES,” Evolutionary and Deterministic Methods for Design, Optimization and Control with Applications to Industrial and Societal Problems, Tadeusz Burczy?ski and Jacques Périaux (Eds.), CIMNE, Barcelona, Spain, 2011, pp. 176–181.
    ISBN: 978-8495999931
  3. Koji Shimoyama, Robust Aerodynamic Design of Mars Exploratory Airplane Wing: With a New Optimization Method, Lambert Academic Publishing, Saarbrücken, Germany, 2010.
    ISBN: 978-3843371933
  4. Koji Shimoyama, Jin Ne Lim, Shinkyu Jeong, Shigeru Obayashi, and Masataka Koishi, “Multi-Objective Robust Optimization Assisted by Response Surface Approximation and Visual Data-Mining,” Multi-Objective Memetic Algorithms, Chi-Keong Goh, Yew-Soon Ong, and Kay Chen Tan (Eds.), Studies in Computational Intelligence, Vol. 171, Springer-Verlag, Berlin / Heidelberg, Germany, 2009, pp. 133–151.
    ISBN: 978-3540880509
  5. Kaisa Miettinen, Kalyanmoy Deb, Johannes Jahn, Wlodzimierz Ogryczak, Koji Shimoyama, and Rudolf Vetschera, “Future Challenges,” Multiobjective Optimization: Interactive and Evolutionary Approaches, Jürgen Branke, Kalyanmoy Deb, Kaisa Miettinen, and Roman S?owi?ski (Eds.), Lecture Notes in Computer Science 5252, Springer-Verlag, Berlin / Heidelberg, Germany, 2008, pp. 435–461.
    ISBN: 978-3540889076
  6. Shigeru Obayashi, Shinkyu Jeong, and Koji Shimoyama, “Multi-Objective Optimization in Aerospace Engineering Design,” Nano-Mega Scale Flow Dynamics for Advanced Aerospace Technology, Shigenao Maruyama and Kazuhiro Nakahashi (Eds.), 21st Century COE Program International COE of Flow Dynamics Lecture Series, Vol. 11, Tohoku University Press, Sendai, Japan, 2007, pp. 159–191.
    ISBN: 978-4861630859
  7. Koji Shimoyama, Kozo Fujii, and Hiroaki Kobayashi, “Improvement of the Optimization Method of the TSTO Configuration – Application of Accurate Aerodynamics,” Computational Fluid Dynamics 2004: Proceedings of the Third International Conference on Computational Fluid Dynamics, ICCFD3, Toronto, 12-16 July 2004, Clinton Groth and David W. Zingg (Eds.), Springer-Verlag, Berlin / Heidelberg, Germany, 2006, pp. 705–710.
    ISBN: 978-3540318002

Patents

  1. Kentaro Kutsukake, Ryota Kikuchi, and Koji Shimoyama, “Mapping Method and Measurement Equipment,” Japanese Patent, No. 6890819, 28 May 2021.
  2. Koji Shimoyama and Kozo Fujii, “Method and Equipment for Solving Robust Optimization Problems,” Japanese Patent, No. 4362572, 28 August 2009.