===affil2:
Hong Kong Polytechnic University
===firstname:
C. T.
===firstname4:

===firstname3:

===lastname2:
Chen
===keyword1:
OTHER
===lastname:
Kelley
===firstname5:

===affil6:

===lastname3:

===email:
tim\_kelley@ncsu.edu
===keyword2:
Applications/Environmental
===keyword_other2:

===lastname6:

===affil5:

===otherauths:

===lastname4:

===affil4:

===lastname7:

===competition:
no
===affil7:

===firstname7:

===postal:
Department of Mathematics, Box 8205
North Carolina State University
Raleigh, NC 2695-8205
===firstname6:

===ABSTRACT:
We discuss the design and implementation of  derivative-free methods for optimization of functions with embedded Monte Carlo simulations. By this we mean that the computation of the function and/or the testing for feasibility depends on a Monte Carlo simulation. Under the assumption that the optimization can control the number of Monte Carlo trials, we prove a probability-one asymptotic convergence result, which provides guidance to a practical implementation. We illustrate the ideas with an application to water resources policy.
===affil3:

===keyword_other1:
Optimization
===lastname5:

===affilother:

===title:
Derivative-Free Optimization of Functions with Embedded Monte Carlo Simulations
===firstname2:
X.