How discretization affects intermittent demand stock management based on simulation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24310%2F23%3A00011493" target="_blank" >RIV/46747885:24310/23:00011493 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.ijsimm.com/Full_Papers/Fulltext2023/text22-4_660.pdf" target="_blank" >https://www.ijsimm.com/Full_Papers/Fulltext2023/text22-4_660.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2507/IJSIMM22-4-660" target="_blank" >10.2507/IJSIMM22-4-660</a>

Jazyk výsledku

angličtina

Název v původním jazyce

How discretization affects intermittent demand stock management based on simulation

Popis výsledku v původním jazyce

This paper is aimed at the development of an alternative combinatorial strategy of reducing searched solution space in intermittent demand stock management based on the past stock movement simulation. The combinatorial strategy involves an adjustable level of the discretization of control variables that are used within a selected inventory control policy. We combine this new strategy with the local search employing linear regression and bootstrapping to bound the reorder point and simulate (Q, R) inventory control policy using randomly generated data. The data is characteristic with an increasing intermittency and a non-zero demand variability. The outputs from simulation experiments show that combining two different strategies of reducing searched solution space brings a significant improvement in the trade-off among the minimal holding and ordering costs, required service level and the consumption of the computational time making the past stock movement simulation to be more applicable in extensive real life tasks.

Název v anglickém jazyce

How discretization affects intermittent demand stock management based on simulation

Popis výsledku anglicky

This paper is aimed at the development of an alternative combinatorial strategy of reducing searched solution space in intermittent demand stock management based on the past stock movement simulation. The combinatorial strategy involves an adjustable level of the discretization of control variables that are used within a selected inventory control policy. We combine this new strategy with the local search employing linear regression and bootstrapping to bound the reorder point and simulate (Q, R) inventory control policy using randomly generated data. The data is characteristic with an increasing intermittency and a non-zero demand variability. The outputs from simulation experiments show that combining two different strategies of reducing searched solution space brings a significant improvement in the trade-off among the minimal holding and ordering costs, required service level and the consumption of the computational time making the past stock movement simulation to be more applicable in extensive real life tasks.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

21100 - Other engineering and technologies

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

International Journal of Simulation Modelling

ISSN

1726-4529

e-ISSN

—

Svazek periodika

vol. 22

Číslo periodika v rámci svazku

no. 4

Stát vydavatele periodika

AT - Rakouská republika

Počet stran výsledku

12

Strana od-do

598-609

Kód UT WoS článku

001129017600003

EID výsledku v databázi Scopus

2-s2.0-85180428399