Eduardo Saliby

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Descriptive Sampling (DS), a Monte Carlo sampling technique based on a deterministic selection of the input values and their random permutation, represents a deep conceptual change on how to carry out a Monte Carlo application. Abandoning the paradigm that a random selection of sample values would be necessary in order to describe random behavior, DS is a(More)
As in any Monte Carlo application, simulation option valuation produces imprecise estimates. In such an application, Descriptive Sampling (DS) has proven to be a powerful Variance Reduction Technique. However, this performance deteriorates as the probability of exercising an option decreases. In the case of out-of-the-money options, the solution is to use(More)
In the last few decades, a lot of company effort has been spent in the optimization of internal efficiency, aiming at cost reduction and competitiveness. Especially over the last decade, there has been a consensus that not only the company, but the whole supply chain in which it fits, is responsible for the success or failure of any business. Therefore,(More)
This paper compares the performance, in terms of convergence rates and precision of the estimates, for six Monte Carlo Simulation sampling methods: Quasi-Monte Carlo using Halton, Sobol, and Faure numeric sequences; Descriptive Sampling, based on the use of deterministic sets and Latin Hypercube Sampling, based on stratified numerical sets. Those methods(More)
Sports had always fascinated humanity. In this context, soccer was taken as a study source. The objective of this paper is to formulate a simulation model to generate estimators for necessary scores to achieve certain places at the final classification ranking of the Brazilian National Soccer Championship. The main data used are the rules of the(More)
The purpose of this paper is to validate and test the adequacy of an analytical expression to calculate proper safety stock levels using simulation techniques. The model refers to a periodic review system and a lot-4-lot replenishment policy, with randomness in forecast errors and in order fulfillment. The simulation model is formulated in a spreadsheet(More)
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