Diffusions for global optimizations
SIAM Journal on Control and Optimization
Diffusion for global optimization in Rn
SIAM Journal on Control and Optimization
SIAM Journal on Applied Mathematics
A global optimization algorithm using stochastic differential equations
ACM Transactions on Mathematical Software (TOMS)
Recursive stochastic algorithms for global optimization in Rd
SIAM Journal on Control and Optimization
Stochastic differential equations (3rd ed.): an introduction with applications
Stochastic differential equations (3rd ed.): an introduction with applications
A Stochastic Algorithm for Constrained Global Optimization
Journal of Global Optimization
A Gradient-based Continuous Method for Large-scale Optimization Problems
Journal of Global Optimization
Linearly Constrained Global Optimization and Stochastic Differential Equations
Journal of Global Optimization
Global optimization of higher order moments in portfolio selection
Journal of Global Optimization
Global optimization of robust chance constrained problems
Journal of Global Optimization
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We establish the convergence of a stochastic global optimization algorithm for general non-convex, smooth functions. The algorithm follows the trajectory of an appropriately defined stochastic differential equation (SDE). In order to achieve feasibility of the trajectory we introduce information from the Lagrange multipliers into the SDE. The analysis is performed in two steps. We first give a characterization of a probability measure (驴) that is defined on the set of global minima of the problem. We then study the transition density associated with the augmented diffusion process and show that its weak limit is given by 驴.