Autors: Popov S. P., Baeva, S. K., Marinova D. M.
Title: Stochastic approach to control of storage stocks in commercial warehouses
Keywords: Stochastic Approach, Stochastic programming, Control of Stor

Abstract: Stochastic programming is an approach for modeling optimization problems that involve uncertainty. Whereas deterministic optimization problems are formulated with known parameters, real world problems almost invariably include parameters which are unknown at the time a decision should be made. When the parameters are uncertain, but assumed to lie in some given set of possible values, one might seek a solution that is feasible for all possible parameter choices and optimizes a given objective function. Such an approach is applied to mathematical model of optimization problem for storage stocks in commercial warehouses. Here probability distributions (e.g., of demand) could be estimated from data that have been collected over time. The aim is to find some policy that is feasible for all (or almost all) the possible parameter realizations and optimizes the expectation of some function of the decisions and the random variables.

References

    Issue

    AIP Conference Proceedings, vol. 2172, pp. 080015-1–080015-13, 2019, Bulgaria, American Institute of Physics

    Full text of the publication

    Цитирания (Citation/s):
    1. Maximilian Barlang, “Integration of Online and Stochastic Optimization for Operational Decision Making in Warehouse Operations”, Scholarly Journal, Proceedings of the IISE Annual Conference & Expo 2024, Volume Editors A. Brown Greer, C. Contardo, J.-M. Frayret, eds., ISBN 978-171387785-1, https://doi.org/10.21872/2024IISE_6079, 2024. - 2024 - в издания, индексирани в Scopus или Web of Science

    Вид: пленарен доклад в международен форум, публикация в реферирано издание, индексирана в Scopus