Algorithms for unconstrained optimization problems via control theory
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Publication:1356095
DOI10.1023/A:1022607507153zbMath0869.49018MaRDI QIDQ1356095
Publication date: 24 August 1997
Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)
algorithmsoptimal controlunconstrained optimizationconvergenceiterative algorithmsLyapunov functionscontinuous-time method
Related Items (10)
Convergence of algorithms in optimization and solutions of nonlinear equations ⋮ Global Dynamical Solvers for Nonlinear Programming Problems ⋮ Feedback stabilization methods for the solution of nonlinear programming problems ⋮ Derivation of coordinate descent algorithms from optimal control theory ⋮ An approach for solving of a moving boundary problem ⋮ A numerical study of basins of attraction of zero-finding neural nets designed using control theory ⋮ Approximate greatest descent methods for optimization with equality constraints ⋮ On the bang-bang control approach via a component-wise line search strategy for unconstrained optimization ⋮ Greatest descent algorithms in unconstrained optimization ⋮ A new method for solving a system of the nonlinear equations
Cites Work
- Stability by Liapunov's direct method. With applications
- ODE versus SQP methods for constrained optimization
- The calculus of variations and optimal control. An introduction
- Singular optimal control problems
- Trajectory-following algorithms for min-max optimization problems
- Terminality, normality, and transversality conditions
- Global convergence of some differential equation algorithms for solving equations involving positive variables
- Necessary Conditions for Singular Extremals Involving Multiple Control Variables
- Stability of Difference Equations and Convergence of Iterative Processes
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