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Simulation basics. - Simulation optimization: an overview. - Response surfaces and neural nets. - Dynamic programming. - Convergence: background material. - Case studies. Covered in detail are model-free optimization techniques - especially designed for those discrete-event, stochastic systems which can be simulated but whose analytical models are difficult to find in closed mathematical forms.
When you click on links to various merchants on this site and make a purchase, this can result in this site earning a commission. Affiliate programs and affiliations include, but are not limited to, the eBay Partner Network.