Open Access
Issue
RAIRO-Oper. Res.
Volume 57, Number 5, September-October 2023
Page(s) 2819 - 2832
DOI https://doi.org/10.1051/ro/2023157
Published online 31 October 2023
  • N. Andrei, An unconstrained optimization test functions collection. Adv. Model. Optim. 10 (2008) 147–161. [MathSciNet] [Google Scholar]
  • B. Barnabas, Mathematics of Fuzzy Sets and Fuzzy Logic. Springer, Berlin, Heidelberg (2013). [Google Scholar]
  • S. Bartles, Numerical Approximation of Partial Differential Equations. Springer (2016). [CrossRef] [Google Scholar]
  • P. Bochev and R.B. Lehoucq, On the finite element solution of the pure neumann problem. SIAM Rev. 47 (2005) 50–66. [CrossRef] [MathSciNet] [Google Scholar]
  • M. Bouchlaghem and E. Mermri, A Uzawa algorithm with multigrid solver for a bilateral obstacle problem. Appl. Math. Comput. 389 (2021) 1125553. [CrossRef] [Google Scholar]
  • A. Boulkhemair, A. Chakib and A. Nachaoui, A shape optimization approach for a class of free boundary problems of Bernoulli type. Appl. Math. 58 (2013) 205–221. [CrossRef] [MathSciNet] [Google Scholar]
  • M. Dashti Ardakani and M. Khodadad, Shape estimation of a cavity by inverse application of the 2D elastostatics problem. Int. J. Comput. Methods 10 (2013) 1350042. [CrossRef] [MathSciNet] [Google Scholar]
  • Y. El Yazidi and A. Ellabib, Augmented Lagrangian approach for a bilateral free boundaries problem. J. Appl. Math. Comput. 67 (2021) 69–88. [CrossRef] [MathSciNet] [Google Scholar]
  • Y. El Yazidi and A. Ellabib, An iterative method for optimal control of bilateral free boundaries problem. Math. Methods Appl. Sci. 44 (2021) 11664–11683. [CrossRef] [MathSciNet] [Google Scholar]
  • Y. El Yazidi and A. Ellabib, A new hybrid method for shape optimization with application to semiconductor equations. Numer. Algebra Control, Optim, 2021. [Google Scholar]
  • Y. Ge, Y. Lin, S. Tao, Q. He, B. Chen and S.-M. Huang, Shape optimization for a tube bank based on the numerical simulation and multi-objective genetic algorithm. Int. J. Therm. Sci. 161 (2021) 106787. [CrossRef] [Google Scholar]
  • M. Hanke, H.W. Engl and A. Neubauer, Regularization of inverse problems. In Vol. 375 of Mathematics and Its Applications, Springer (2000). [Google Scholar]
  • J. Harris, An Introduction to Fuzzy Logic Applications. Springer, Netherlands (2000). [CrossRef] [Google Scholar]
  • J. Haslinger and R.A.E. Mäkinen, Introduction to Shape Optimization: Theory, Approximation, and Computation. SIAM (2003). [CrossRef] [Google Scholar]
  • M. Hinze, B. Kaltenbacher and T.N.T. Quyen, Identifying conductivity in electrical impedance tomography with total variation regularization. Numer. Math. 138 (2018) 723–765. [CrossRef] [MathSciNet] [Google Scholar]
  • C.H. Huang and C.C. Shih, A shape identification problem in estimating simultaneously two interfacial configurations in a multiple region domain. Appl. Therm. Eng. 26 (2006) 77–88. [CrossRef] [Google Scholar]
  • S. Khan, M. Kamran, O.U. Rehman, L. Liu and S. Yang, A modified PSO algorithm with dynamic parameters for solving complex engineering design problem. Int. J. Comput. Math. 95 (2018) 2308–2329. [CrossRef] [Google Scholar]
  • S. Koike, Regularity of solutions of obstacle problems -old & new-. In Vol. 346 of Nonlinear Partial Differential Equations for Future Applications, edited by S. Koike, H. Kozono, T. Ogawa, S. Sakaguchi, PDEFA 2017. Springer Proceedings in Mathematics & Statistics, Springer, Singapore (2017). [Google Scholar]
  • J.C. Liu, Shape Reconstruction of Conductivity Interface Problems. Int. J. Comput. Methods 16 (2018) 1850092. [Google Scholar]
  • C. Maurice, Particle Swarm Optimization. ISTE (2006). [Google Scholar]
  • M.H. Mozaffari, M. Khodadad and M. Dashti Ardakani, Simultaneous identification of multi-irregular interfacial boundary configurations in non-homogeneous body using surface displacement measurements. J. Mech. Eng. Sci. 231 (2016) 1–12. [Google Scholar]
  • A. Nejat, P. Mirzabeygi and P.M. Shariat, Airfoil shape optimization using improved Multiobjective Territorial Particle Swarm algorithm with the objective of improving stall characteristics. Struct. Multidiscipl. Optim. 49 (2014) 953–967. [CrossRef] [Google Scholar]
  • H. Prautzsch, W. Boehm and M. Paluszny, Bézier and B-Spline Techniques. Springer, Berlin, Heidelberg (2002). [CrossRef] [Google Scholar]
  • S. Salhi, Heuristic Search the Emerging Science of Problem Solving. Palgrave Macmillan (2017). [CrossRef] [Google Scholar]
  • F. Valdez, J.C. Vazquez, P. Melin and O. Castillo, Comparative study of the use of fuzzy logic in improving particle swarm optimization variants for mathematical functions using co-evolution. Appl. Soft Comput. 52 (2017) 1070–1083. [CrossRef] [Google Scholar]
  • C.R. Vogel, Computational methods for inverse problems. In: Society for Industrial and Applied Mathematics (2002) 195. [Google Scholar]
  • C. Wang, J.M. Koh, T. Yu, N.G. Xie and K.H. Cheong, Material and shape optimization of bi-directional functionally graded plates by GIGA and an improved multi-objective particle swarm optimization algorithm. Comput. Methods Appl. Mech. Eng. 366 (2020) 113017. [CrossRef] [Google Scholar]
  • P. Wu, W. Yuan, L. Ji, L. Zhou, Z. Zhou, W. Feng and Y. Guo, Missile aerodynamic shape optimization design using deep neural networks. Aerosp. Sci. Technol. 126 (2022) 107640. [CrossRef] [Google Scholar]
  • X. Zhang, F. Xie, T. Ji, Z. Zhu and Y. Zheng, Multi-fidelity deep neural network surrogate model for aerodynamic shape optimization. Comput. Methods Appl. Mech. Eng. 373 (2021) 113485. [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.