...... 91/10/31TE S. FUNDING NUMBERS Parallel Global Optimization: Numerical Methods, Dynamic Scheduling Methods, and Application to Molecular Configuration 1Zc,.O3.. r "l'-- 0 0 i'

The view, opinions and/or findings contained in this report are those of the author(s) and should not be construed as an official Department of the Army position, policy, or decision, unless so designated by other documentation. 12a. DISTRIBUTION /AVAILABILITY STATEMENT 12b. DISTRIBUTION CODE Approved for public release; distribution unlimited. 13. ABSTRACT (Maximum 200 words) Global optimization problems are computationally intensive problems that arise in many important applications. The solution of very large practical global optimization problems, which may have thousands of variables and huge numbers of local minimizers, is not yet possible. It will require efficient numerical algorithms that take advantage of the properties of the particular application, as well as efficient utilization of the fastest available computers, which will almost certainly be highly parallel machines. This paper summarizes our research efforts in this direction. First, we describe general purpose adaptive, asynchronous parallel stochastic global optimization methods that we have developed, and our computational experience with them. Second, we describe several alternative dynamic scheduling algorithms that are required to control such dynamic parallel algorithms on distributed memory multiprocessors, and compare their performance in the context of our parallel global optimization methods. Third, we discuss th