Abstract
Due to simulation models are stochastic systems, how to account for the noise in simulation model is a rigorous issue in the field of simulation optimization. We proposed a framework, which merging the Ranking & Selection into ITO algorithm for solving simulation optimization problems in this paper. When the probability of correct choice and the parameters of indifference zone are given, Ranking & Selection + ITO algorithm can allocate the number of evaluations that each alternative needed automatically, and it can evaluate individuals by a smaller budget.
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Dong, W., Yu, R., Lei, M. (2010). Merging the Ranking and Selection into ITO Algorithm for Simulation Optimization. In: Cai, Z., Tong, H., Kang, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2010. Communications in Computer and Information Science, vol 107. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16388-3_10
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DOI: https://doi.org/10.1007/978-3-642-16388-3_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16387-6
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