An Adaptive Exploration-Exploitation Algorithm for Constructing Metamodels in Random Simulation Using a Novel Sequential Experimental Design

Abstract

In this article, we propose a novel algorithm for sequential design of metamodels in random simulation, which combines the exploration capability of most one-shot space-filling designs with the exploitation feature of common sequential designs. The algorithm continuously maintains a balance between the exploration and the exploitation search throughout the search process in a sequential and adaptive manner. The numerical results indicate that the proposed approach is superior to one of the existing well-known sequential designs in terms of both the computational efficiency and speed in generating efficient experimental designs.

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