Inventory management of goods is an integral part of logistics systems; common to various economic sectors such as industry, agriculture and trade; and independent of production volume. In general, as companies seek to minimize economic losses, studies on problems of multi-agent inventory have increased in recent years. A multi-agent inventory problem is a situation in which several agents face individual inventory problems and agree to coordinate their orders with the objective of reducing their costs. The R package Inventorymodel allows the determination of both the optimal policy for some inventory situations with deterministic demands and the allocation of costs from a game-theoretic perspective. The required calculations may be computed for any number of agents although the computational complexity of this class of problems when the involved agents enlarge is not reduced. In this work, the different possibilities that the package offers are described and some examples of usage are also demonstrated.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2018-023.zip
Inventorymodel, e1071, GameTheoryAllocation
Cluster, Distributions, Environmetrics, MachineLearning, Multivariate, Psychometrics
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
For attribution, please cite this work as
Saavedra-Nieves, "Inventorymodel: an R Package for Centralized Inventory Problems", The R Journal, 2018
BibTeX citation
@article{RJ-2018-023,
author = {Saavedra-Nieves, Alejandro},
title = {Inventorymodel: an R Package for Centralized Inventory Problems},
journal = {The R Journal},
year = {2018},
note = {https://doi.org/10.32614/RJ-2018-023},
doi = {10.32614/RJ-2018-023},
volume = {10},
issue = {1},
issn = {2073-4859},
pages = {200-217}
}