Inventory Optimization using Simulation Approach

Inventory creates a significant cost to a firm in the form of the ordering cost, shortage cost, holding cost and also the cost of the goods itself. Managing inventory is always a big challenge for firms in order to balance these operating costs and maintain customer’s service. In this paper, a case...

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Formato:	article
Lenguaje:	EN
Publicado:	Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis 2018
Materias:	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995
Acceso en línea:	https://doaj.org/article/34c88ba4f64341a68636f51f42aee2f2
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spelling	oai:doaj.org-article:34c88ba4f64341a68636f51f42aee2f22021-11-06T02:26:33ZInventory Optimization using Simulation Approach2600-8793https://doaj.org/article/34c88ba4f64341a68636f51f42aee2f22018-11-01T00:00:00Zhttp://repeater.my/index.php/jcrinn/article/view/93https://doaj.org/toc/2600-8793 Inventory creates a significant cost to a firm in the form of the ordering cost, shortage cost, holding cost and also the cost of the goods itself. Managing inventory is always a big challenge for firms in order to balance these operating costs and maintain customer’s service. In this paper, a case study of an electronics manufacturing firm was used to illustrate the use of the Monte Carlo simulation to improve the current inventory system for sensor cable. A simulation model mimicking the current inventory system was developed, and used to study the current system and alternative reorder point policies. Various reorder points were experimented to determine the reorder policy that results in the lowest average total inventory cost per week. The simulation experiments allow the decision maker to make good purchasing decisions in order to avoid ordering excessive raw materials which lead to higher inventory cost to the company. Keywords: inventory, optimization, Monte Carlo Simulation Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA PerlisarticleProbabilities. Mathematical statisticsQA273-280TechnologyTTechnology (General)T1-995ENJournal of Computing Research and Innovation, Vol 3, Iss 2 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995
spellingShingle	Probabilities. Mathematical statistics QA273-280 Technology T Technology (General) T1-995 Inventory Optimization using Simulation Approach
description	Inventory creates a significant cost to a firm in the form of the ordering cost, shortage cost, holding cost and also the cost of the goods itself. Managing inventory is always a big challenge for firms in order to balance these operating costs and maintain customer’s service. In this paper, a case study of an electronics manufacturing firm was used to illustrate the use of the Monte Carlo simulation to improve the current inventory system for sensor cable. A simulation model mimicking the current inventory system was developed, and used to study the current system and alternative reorder point policies. Various reorder points were experimented to determine the reorder policy that results in the lowest average total inventory cost per week. The simulation experiments allow the decision maker to make good purchasing decisions in order to avoid ordering excessive raw materials which lead to higher inventory cost to the company. Keywords: inventory, optimization, Monte Carlo Simulation
format	article
title	Inventory Optimization using Simulation Approach
title_short	Inventory Optimization using Simulation Approach
title_full	Inventory Optimization using Simulation Approach
title_fullStr	Inventory Optimization using Simulation Approach
title_full_unstemmed	Inventory Optimization using Simulation Approach
title_sort	inventory optimization using simulation approach
publisher	Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perlis
publishDate	2018
url	https://doaj.org/article/34c88ba4f64341a68636f51f42aee2f2
_version_	1718443969995603968

Inventory Optimization using Simulation Approach

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