A1170
Title: A simulation-based approach for the optimal order size of new products under uncertainty on forecast parameters
Authors: David Fernando Munoz - Instituto Tecnologico Autonomo de Mexico (Mexico) [presenting]
Abstract: A Bayesian approach is applied to determine the optimal order size for seasonal or new products using different optimality criteria to incorporate uncertainty in demand forecast parameters. The methodology is illustrated through two relevant criteria: the newsboy problem and the capacity index criterion. Experiments are conducted with a forecast model that has an analytical solution for the posterior distribution, and results illustrate the estimation of optimal order size using Monte Carlo simulation. Monte Carlo simulation is appealing when the complexity of the forecast model prevents obtaining optimal order sizes through analytical solution or more efficient numerical algorithms.
