INDUSTRIAL ENGINEERING AND
OPERATIONS RESEARCH
PRESENTS
IEOR SPECIAL SEMINAR
TUESDAY
A Model Reference Adaptive Search Method for Global Optimization
Jiaqiao Hu
Abstract:
We propose a novel general framework called Model
Reference Adaptive Search (MRAS) for solving global optimization problems. The
method iteratively updates a parameterized probability distribution on the
solution space so that the sequence of candidate solutions generated from this
distribution will converge asymptotically to the global optimum. We provide a
particular instantiation of the framework and establish its global convergence
properties in both continuous and discrete (combinatorial) domains. In
addition, we explore the relationship between the recently proposed
Cross-Entropy (CE) method and MRAS, and show that the CE method can also be
interpreted as an instance of the MRAS framework. The extension of the MRAS
method to stochastic optimization problems is also discussed. Finally, we carry
out numerical experiments to investigate the performance of the method.
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