A stochastic method for global optimization

A Model Reference Adaptive Search Method for Stochastic Global Optimization

We propose a new method called Stochastic Model Reference Adaptive Search (SMRAS) for finding a global optimal solution to a stochastic optimization problem in situations where the objective functions cannot be evaluated exactly, but can be estimated with some noise (or uncertainty), e.g., via simulation. SMRAS is a generalization of the recently proposed Model Reference Adaptive Search (MRAS) ...

A branch and bound method for stochastic global optimization

A stochastic version of the branch and bound method is proposed for solving stochastic global optimization problems. The method, instead of deterministic bounds, uses stochastic upper and lower estimates of the optimal value of subproblems, to guide the partitioning process. Almost sure convergence of the method is proved and random accuracy estimates derived. Methods for constructing random bo...

A Stochastic Optimization Model for Groundwater Management

A Stochastic Optimization Model for Groundwater Management

Stochastic Global Optimization

Stochastic global optimization methods are methods for solving a global optimization problem incorporating probabilistic (stochastic) elements, either in the problem data (the objective function, the constraints, etc.), or in the algorithm itself, or in both. Global optimization is a very important part of applied mathematics and computer science. The importance of global optimization is primar...