The task of determining the optimal sizes of spare parts for an auto-service enterprise based on the maximum profit criterion for a discrete distribution of demand is formulated as a problem of quadratic programming with linear constraints. To calculate the probabilistic measure of the distribution of the values of the demand vector components, an approximation is used of the empirical distribution function of the demand components by hyper-Erlanger distribution functions, and the subsequent calculation of the corresponding distribution densities.
| Published in | Science Journal of Business and Management (Volume 5, Issue 4) |
| DOI | 10.11648/j.sjbm.20170504.15 |
| Page(s) | 169-174 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2017. Published by Science Publishing Group |
Spare Parts, Storage Costs, Costs for Fulfilling Orders, Distribution
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APA Style
Karimov Nijat Ashraf. (2017). A Logistical Approach to Managing the Resources of Multi Nomenclature Spare Parts of a Corporate Car Service in Conditions of Risk and Uncertainty of Demand. Science Journal of Business and Management, 5(4), 169-174. https://doi.org/10.11648/j.sjbm.20170504.15
ACS Style
Karimov Nijat Ashraf. A Logistical Approach to Managing the Resources of Multi Nomenclature Spare Parts of a Corporate Car Service in Conditions of Risk and Uncertainty of Demand. Sci. J. Bus. Manag. 2017, 5(4), 169-174. doi: 10.11648/j.sjbm.20170504.15
AMA Style
Karimov Nijat Ashraf. A Logistical Approach to Managing the Resources of Multi Nomenclature Spare Parts of a Corporate Car Service in Conditions of Risk and Uncertainty of Demand. Sci J Bus Manag. 2017;5(4):169-174. doi: 10.11648/j.sjbm.20170504.15
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Download@article{10.11648/j.sjbm.20170504.15,
author = {Karimov Nijat Ashraf},
title = {A Logistical Approach to Managing the Resources of Multi Nomenclature Spare Parts of a Corporate Car Service in Conditions of Risk and Uncertainty of Demand},
journal = {Science Journal of Business and Management},
volume = {5},
number = {4},
pages = {169-174},
doi = {10.11648/j.sjbm.20170504.15},
url = {https://doi.org/10.11648/j.sjbm.20170504.15},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.sjbm.20170504.15},
abstract = {The task of determining the optimal sizes of spare parts for an auto-service enterprise based on the maximum profit criterion for a discrete distribution of demand is formulated as a problem of quadratic programming with linear constraints. To calculate the probabilistic measure of the distribution of the values of the demand vector components, an approximation is used of the empirical distribution function of the demand components by hyper-Erlanger distribution functions, and the subsequent calculation of the corresponding distribution densities.},
year = {2017}
}
TY - JOUR T1 - A Logistical Approach to Managing the Resources of Multi Nomenclature Spare Parts of a Corporate Car Service in Conditions of Risk and Uncertainty of Demand AU - Karimov Nijat Ashraf Y1 - 2017/08/15 PY - 2017 N1 - https://doi.org/10.11648/j.sjbm.20170504.15 DO - 10.11648/j.sjbm.20170504.15 T2 - Science Journal of Business and Management JF - Science Journal of Business and Management JO - Science Journal of Business and Management SP - 169 EP - 174 PB - Science Publishing Group SN - 2331-0634 UR - https://doi.org/10.11648/j.sjbm.20170504.15 AB - The task of determining the optimal sizes of spare parts for an auto-service enterprise based on the maximum profit criterion for a discrete distribution of demand is formulated as a problem of quadratic programming with linear constraints. To calculate the probabilistic measure of the distribution of the values of the demand vector components, an approximation is used of the empirical distribution function of the demand components by hyper-Erlanger distribution functions, and the subsequent calculation of the corresponding distribution densities. VL - 5 IS - 4 ER -
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