17th International Symposium on
Mathematical Theory of Networks and Systems
Kyoto International Conference Hall, Kyoto, Japan, July 24-28, 2006

MTNS 2006 Paper Abstract

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Paper MoP08.2

Fu, Michael (Univ. of Maryland), Marcus, Steven (Univ. of Maryland), Hu, Jiaqiao (Univ. of Maryland)

Model-Based Randomized Methods for Global Optimization

Scheduled for presentation during the Mini-Symposium "Randomized and Probabilistic Techniques for Complex Systems Design" (MoP08), Monday, July 24, 2006, 15:45−16:10, Room I

17th International Symposium on Mathematical Theory of Networks and Systems, July 24-28, 2006, Kyoto, Japan

This information is tentative and subject to change. Compiled on March 28, 2024

Keywords Nonsmooth optimization, Iterative methods

Abstract

We survey some recently introduced randomized search methods for global optimization based on sampling from an underlying probability distribution "model" on the decision parameter space. In this approach, the model is updated iteratively after evaluating the performance of the samples at each iteration. Such model-based methods include estimation of distribution algorithms (EDAs), the cross-entropy method (CEM), and the recently proposed model reference adaptive search (MRAS).