A gradient descent akin method for constrained optimization: algorithms and applications
暂无分享,去创建一个
Y. Ye | N. Gauger | K. Bletzinger | Long Chen
[1] J. Martins,et al. Engineering Design Optimization , 2021 .
[2] Antonis Papachristodoulou,et al. Chordal and factor-width decompositions for scalable semidefinite and polynomial optimization , 2021, Annu. Rev. Control..
[3] Michael A. Saunders,et al. Large-scale Optimization with Linear Equality Constraints using Reduced Compact Representation , 2021, SIAM J. Sci. Comput..
[4] F. Barthold,et al. Shape optimization of the X0-specimen: theory, numerical simulation and experimental verification , 2020, Computational Mechanics.
[5] Brendan O'Donoghue. Operator Splitting for a Homogeneous Embedding of the Linear Complementarity Problem , 2020, SIAM J. Optim..
[6] G. Allaire,et al. Null space gradient flows for constrained optimization with applications to shape optimization , 2020, ESAIM: Control, Optimisation and Calculus of Variations.
[7] Grigorios Koulouras,et al. Applications of Wireless Sensor Networks: An Up-to-Date Survey , 2020, Applied System Innovation.
[8] Simon W. Funke,et al. Automatic shape derivatives for transient PDEs in FEniCS and Firedrake , 2020, 2001.10058.
[9] Roland Wüchner,et al. A partitioned scheme for adjoint shape sensitivity analysis of fluid–structure interactions involving non-matching meshes , 2019, Optim. Methods Softw..
[10] Amir Ali Ahmadi,et al. A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics , 2019, Annu. Rev. Control. Robotics Auton. Syst..
[11] Long Chen,et al. A modified search direction method for inequality constrained optimization problems using the singular-value decomposition of normalized response gradients , 2019, Structural and Multidisciplinary Optimization.
[12] Radu Ioan Bot,et al. A primal-dual dynamical approach to structured convex minimization problems , 2019, 1905.08290.
[13] Michael I. Jordan. DYNAMICAL, SYMPLECTIC AND STOCHASTIC PERSPECTIVES ON GRADIENT-BASED OPTIMIZATION , 2019, Proceedings of the International Congress of Mathematicians (ICM 2018).
[14] Daniel Luft,et al. Efficient Techniques for Shape Optimization with Variational Inequalities Using Adjoints , 2019, SIAM J. Optim..
[15] Kresimir Mihic,et al. Managing randomization in the multi-block alternating direction method of multipliers for quadratic optimization , 2019, Math. Program. Comput..
[16] Peter Eberhard,et al. Geometric element parameterization and parametric model order reduction in finite element based shape optimization , 2018, Computational Mechanics.
[17] R. Michael Buehrer,et al. Collaborative Sensor Network Localization: Algorithms and Practical Issues , 2018, Proceedings of the IEEE.
[18] M. Montaz Ali,et al. A Trajectory-Based Method for Constrained Nonlinear Optimization Problems , 2018, J. Optim. Theory Appl..
[19] Sanjeev Arora,et al. On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization , 2018, ICML.
[20] Stephen P. Boyd,et al. OSQP: an operator splitting solver for quadratic programs , 2017, Mathematical Programming Computation.
[21] Kim-Chuan Toh,et al. SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0) , 2017, Optim. Methods Softw..
[22] S. Gaubert,et al. Log-Barrier Interior Point Methods Are Not Strongly Polynomial , 2017, SIAM Journal on applied algebra and geometry.
[23] Danda B. Rawat,et al. Advances on localization techniques for wireless sensor networks: A survey , 2016, Comput. Networks.
[24] Michal Kocvara,et al. Primal-Dual Interior Point Multigrid Method for Topology Optimization , 2016, SIAM J. Sci. Comput..
[25] Tim A. Albring,et al. Efficient Aerodynamic Design using the Discrete Adjoint Method in SU2 , 2016 .
[26] Dimitri P. Bertsekas,et al. Convex Optimization Algorithms , 2015 .
[27] Graeme J. Kennedy. Large-Scale Multimaterial Topology Optimization for Additive Manufacturing , 2015 .
[28] Stephen P. Boyd,et al. A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights , 2014, J. Mach. Learn. Res..
[29] V. Schulz,et al. Towards a Lagrange–Newton Approach for PDE Constrained Shape Optimization , 2014, 1405.3266.
[30] Graeme J. Kennedy,et al. Scalable Parallel Approach for High-Fidelity Steady-State Aeroelastic Analysis and Adjoint Derivative Computations , 2014 .
[31] V. Schulz,et al. Three-Dimensional Large-Scale Aerodynamic Shape Optimization Based on Shape Calculus , 2013 .
[32] Joaquim R. R. A. Martins,et al. Multidisciplinary design optimization: A survey of architectures , 2013 .
[33] Jacek Gondzio,et al. Interior point methods 25 years later , 2012, Eur. J. Oper. Res..
[34] Emmanuel J. Candès,et al. Adaptive Restart for Accelerated Gradient Schemes , 2012, Foundations of Computational Mathematics.
[35] Claudia Schillings,et al. Efficient shape optimization for certain and uncertain aerodynamic design , 2011 .
[36] Joaquim R. R. A. Martins,et al. pyOpt: a Python-based object-oriented framework for nonlinear constrained optimization , 2011, Structural and Multidisciplinary Optimization.
[37] Tomi Räty,et al. Survey on Contemporary Remote Surveillance Systems for Public Safety , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).
[38] Zhi-Quan Luo,et al. Semidefinite Relaxation of Quadratic Optimization Problems , 2010, IEEE Signal Processing Magazine.
[39] Jason E. Hicken,et al. Aerodynamic Optimization Algorithm with Integrated Geometry Parameterization and Mesh Movement , 2010 .
[40] Stephen P. Boyd,et al. Convex Optimization , 2010, IEEE Transactions on Automatic Control.
[41] Jože Korelc,et al. Automation of primal and sensitivity analysis of transient coupled problems , 2009 .
[42] Harbir Antil,et al. Adaptive Path Following Primal Dual Interior Point Methods for Shape Optimization of Linear and Nonlinear Stokes Flow Problems , 2009, LSSC.
[43] Masakazu Kojima,et al. Exploiting Sparsity in SDP Relaxation for Sensor Network Localization , 2009, SIAM J. Optim..
[44] Stephen P. Boyd,et al. Further Relaxations of the Semidefinite Programming Approach to Sensor Network Localization , 2008, SIAM J. Optim..
[45] Yinyu Ye,et al. Algorithm 875: DSDP5—software for semidefinite programming , 2008, TOMS.
[46] Naomi Ehrich Leonard,et al. Collective Motion, Sensor Networks, and Ocean Sampling , 2007, Proceedings of the IEEE.
[47] Harbir Antil,et al. Path-following primal-dual interior-point methods for shape optimization of stationary flow problems , 2007, J. Num. Math..
[48] Jorge Cortés,et al. Finite-time convergent gradient flows with applications to network consensus , 2006, Autom..
[49] Yinyu Ye,et al. Semidefinite programming based algorithms for sensor network localization , 2006, TOSN.
[50] D. Puccinelli,et al. Wireless sensor networks: applications and challenges of ubiquitous sensing , 2005, IEEE Circuits and Systems Magazine.
[51] Ling-Jyh Chen,et al. Reliable sensor networks for planet exploration , 2005, Proceedings. 2005 IEEE Networking, Sensing and Control, 2005..
[52] Anthony Man-Cho So,et al. Theory of semidefinite programming for Sensor Network Localization , 2005, SODA '05.
[53] Yinyu Ye,et al. Semidefinite programming for ad hoc wireless sensor network localization , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.
[54] G. Allaire,et al. Structural optimization using sensitivity analysis and a level-set method , 2004 .
[55] Michael Stingl,et al. PENNON: A code for convex nonlinear and semidefinite programming , 2003, Optim. Methods Softw..
[56] X. Q. Yang,et al. A Unified Gradient Flow Approach to Constrained Nonlinear Optimization Problems , 2003, Comput. Optim. Appl..
[57] Anders Forsgren,et al. Interior Methods for Nonlinear Optimization , 2002, SIAM Rev..
[58] Ian F. Akyildiz,et al. Wireless sensor networks: a survey , 2002, Comput. Networks.
[59] G. Dias,et al. Shape structural optimization with an interior point nonlinear programming algorithm , 2000 .
[60] Volker Schulz,et al. Interior point multigrid methods for topology optimization , 2000 .
[61] Alex M. Andrew. Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (2nd edition) , 2000 .
[62] H. Attouch,et al. THE HEAVY BALL WITH FRICTION METHOD, I. THE CONTINUOUS DYNAMICAL SYSTEM: GLOBAL EXPLORATION OF THE LOCAL MINIMA OF A REAL-VALUED FUNCTION BY ASYMPTOTIC ANALYSIS OF A DISSIPATIVE DYNAMICAL SYSTEM , 2000 .
[63] T. Vicsek,et al. Collective Motion , 1999, physics/9902023.
[64] Florian Jarre,et al. Optimal Truss Design by Interior-Point Methods , 1998, SIAM J. Optim..
[65] David P. Williamson,et al. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming , 1995, JACM.
[66] Farid Alizadeh,et al. Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization , 1995, SIAM J. Optim..
[67] N. Stander,et al. On the robustness and efficiency of the SAM algorithm for structural optimization , 1995 .
[68] E. D. Klerk,et al. A feasible descent cone method for linearly constrained minimization problems , 1994 .
[69] U. Helmke,et al. Optimization and Dynamical Systems , 1994, Proceedings of the IEEE.
[70] Jan A. Snyman,et al. A new first‐order interior feasible direction method for structural optimization , 1993 .
[71] R. Haftka,et al. On options for interdisciplinary analysis and design optimization , 1992 .
[72] D. Bayer,et al. The nonlinear geometry of linear programming. I. Affine and projective scaling trajectories , 1989 .
[73] Jasbir S. Arora,et al. Introduction to Optimum Design , 1988 .
[74] J. Snyman,et al. A multi-start global minimization algorithm with dynamic search trajectories , 1987 .
[75] K. Svanberg. The method of moving asymptotes—a new method for structural optimization , 1987 .
[76] A. Griewank. Generalized descent for global optimization , 1981 .
[77] C. Botsaris. Differential gradient methods , 1978 .
[78] K. Linkwitz,et al. Einige Bemerkungen zur Berechnung von vorgespannten Seilnetzkonstruktionen , 1971 .
[79] M. J. D. Powell,et al. Nonlinear Programming—Sequential Unconstrained Minimization Techniques , 1969 .
[80] J. B. Rosen. The Gradient Projection Method for Nonlinear Programming. Part I. Linear Constraints , 1960 .
[81] Michael I. Jordan,et al. A Lyapunov Analysis of Accelerated Methods in Optimization , 2021, J. Mach. Learn. Res..
[82] Nikolaos Ploskas,et al. Interior Point Methods , 2017 .
[83] Phillipp Kaestner,et al. Linear And Nonlinear Programming , 2016 .
[84] R. Rao,et al. Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems , 2016 .
[85] Michael R Wisnom,et al. 56th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference , 2015 .
[86] John T. Hwang. A Modular Approach to Large-scale Design Optimization of Aerospace Systems. , 2015 .
[87] Joaquim R. R. A. Martins,et al. Comparison of inexact- and quasi-Newton algorithms for aerodynamic shape optimization , 2015 .
[88] Kai-Uwe Bletzinger,et al. The Vertex Morphing method for node-based shape optimization , 2014 .
[89] Uwe Naumann,et al. A Discrete Adjoint Model for OpenFOAM , 2013, ICCS.
[90] Makoto Yamashita,et al. Latest Developments in the SDPA Family for Solving Large-Scale SDPs , 2012 .
[91] F. Verhulst. Differential Equations and Dynamical Systems , 2012 .
[92] Kai-Uwe Bletzinger,et al. Free Shape Optimal Design of Structures , 2011 .
[93] Y. Ye,et al. A Distributed Method for Solving Semidefinite Programs Arising from Ad Hoc Wireless Sensor Network Localization , 2006 .
[94] Jing J. Liang,et al. Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization , 2006 .
[95] Yinyu Ye,et al. DSDP5: Software for Semidefinite Programming , 2005 .
[96] K. N. Seetharamu,et al. The Finite Element Method , 2005 .
[97] J. Lofberg,et al. YALMIP : a toolbox for modeling and optimization in MATLAB , 2004, 2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508).
[98] Raino A. E. Mäkinen,et al. Introduction to shape optimization - theory, approximation, and computation , 2003, Advances in design and control.
[99] Sven Leyffer,et al. Nonlinear programming without a penalty function , 2002, Math. Program..
[100] Knud D. Andersen,et al. The Mosek Interior Point Optimizer for Linear Programming: An Implementation of the Homogeneous Algorithm , 2000 .
[101] Andreas Griewank,et al. Evaluating derivatives - principles and techniques of algorithmic differentiation, Second Edition , 2000, Frontiers in applied mathematics.
[102] Y. Ye,et al. Semidefinite programming relaxations of nonconvex quadratic optimization , 2000 .
[103] Michael M. Kostreva,et al. Methods of Feasible Directions: A Review , 2000 .
[104] Jorge Nocedal,et al. A trust region method based on interior point techniques for nonlinear programming , 2000, Math. Program..
[105] Walter Murray,et al. An efficient gradient flow method for unconstrained optimization , 1998 .
[106] Y. Ye. Interior point algorithms - theory and analysis , 1998, Wiley-Interscience series in discrete mathematics and optimization.
[107] G. Allaire,et al. Shape optimization by the homogenization method , 1997 .
[108] Immo Diener,et al. Trajectory Methods in Global Optimization , 1995 .
[109] Jan Sokolowski,et al. Introduction to shape optimization , 1992 .
[110] J. Lagarias. The nonlinear geometry of linear programming. III. Projective Legendre transform coordinates and Hilbert geometry , 1990 .
[111] Y. Nesterov. A method for solving the convex programming problem with convergence rate O(1/k^2) , 1983 .
[112] G. Zoutendijk,et al. Methods of feasible directions : a study in linear and non-linear programming , 1960 .