Abstract
The best choice problem is an important class of the theory of optimal stopping rules. In this article, we present the Cross-Entropy method for solving the multiple best choice problem with the minimal expected ranks of selected objects. We also compare computation results by Cross-Entropy method with results by the genetic algorithm. Computational results showed that the Cross-Entropy method is producing high-quality solution.
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Polushina, T.V. (2010). Estimating Optimal Stopping Rules in the Multiple Best Choice Problem with Minimal Summarized Rank via the Cross-Entropy Method. In: Chen, Yp. (eds) Exploitation of Linkage Learning in Evolutionary Algorithms. Evolutionary Learning and Optimization, vol 3. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12834-9_11
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DOI: https://doi.org/10.1007/978-3-642-12834-9_11
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