Inventory optimization model parameter search speed-up through similarity reduction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F21%3A10245331" target="_blank" >RIV/61989100:27740/21:10245331 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-51992-6_9" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-51992-6_9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-51992-6_9" target="_blank" >10.1007/978-3-030-51992-6_9</a>

Result language
angličtina
Original language name
Inventory optimization model parameter search speed-up through similarity reduction
Original language description
This paper is concerned with finding near optimal parameters for the inventory optimization model on large dataset. It is shown that our proposed method allows for very good model parameter estimation with great reduction in computation time. Model developed in cooperation with K2 atmitec s.r.o. company has four input parameters which must be set before the run. These parameters are estimated through computationally complex simulations by hyperparameter search. Since it is impossible to make grid search of the optimal parameters for all the input time series, it is necessary to approximate the parameters settings. This approximation is done through similarity search and computation of optimal parameters on the most central objects. Additionally, parameter estimation is improved by the clustering of time series and the results are upgraded by the new estimations. (C) Springer Nature Switzerland AG 2021.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Advances in Intelligent Systems and Computing. Volume 1221
ISBN
978-3-030-51991-9
ISSN
2194-5357
e-ISSN
2194-5365
Number of pages
13
Pages from-to
102-114
Publisher name
Springer
Place of publication
Cham
Event location
Arad
Event date
Sep 13, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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