MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTS
In general, companies have inventory stored in warehouses to be used or sold in the future. To optimize inventory, companies require a model to determine the appropriate order quantity and optimal reorder timing to minimize total inventory costs. To stay within the set capacity, several factors need...
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Universitas Pattimura
2024-07-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12759 |
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| author | Claresta Tirta Saputera Gunawan Dharma Lesmono Daniel Salim |
| author_facet | Claresta Tirta Saputera Gunawan Dharma Lesmono Daniel Salim |
| author_sort | Claresta Tirta Saputera Gunawan |
| collection | DOAJ |
| description | In general, companies have inventory stored in warehouses to be used or sold in the future. To optimize inventory, companies require a model to determine the appropriate order quantity and optimal reorder timing to minimize total inventory costs. To stay within the set capacity, several factors need to be considered in inventory management, such as a product's shelf life, warehouse capacity, and capital. On the other hand, suppliers may offer discounts, and companies tend to take advantage of them. However, they must consider the warehouse capacity and capital availability. This paper constructs two probabilistic multi-item inventory models, considering discounts, expiration, warehouse capacity, and capital constraint. The first model considers all-unit discounts, while the second deals with incremental discounts. We consider three items to be managed and examine three replenishment policies, namely individual order, joint order, and a combined policy of individual and joint order, to minimize the total inventory cost. Sensitivity analysis is performed on the joint order policy to determine the influence of parameter values' changes on the reorder time and total inventory cost. |
| format | Article |
| id | doaj-art-15f8c7ec072f4affb75d0bfc5f09e70b |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-15f8c7ec072f4affb75d0bfc5f09e70b2025-08-20T03:49:07ZengUniversitas PattimuraBarekeng1978-72272615-30172024-07-011832001201410.30598/barekengvol18iss3pp2001-201412759MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTSClaresta Tirta Saputera Gunawan0Dharma Lesmono1Daniel Salim2Center for Mathematics and Society, Department of Mathematics, Faculty of Information Technology and Sciences, Universitas Katolik Parahyangan, IndonesiaCenter for Mathematics and Society, Department of Mathematics, Faculty of Information Technology and Sciences, Universitas Katolik Parahyangan, IndonesiaCenter for Mathematics and Society, Department of Mathematics, Faculty of Information Technology and Sciences, Universitas Katolik Parahyangan, IndonesiaIn general, companies have inventory stored in warehouses to be used or sold in the future. To optimize inventory, companies require a model to determine the appropriate order quantity and optimal reorder timing to minimize total inventory costs. To stay within the set capacity, several factors need to be considered in inventory management, such as a product's shelf life, warehouse capacity, and capital. On the other hand, suppliers may offer discounts, and companies tend to take advantage of them. However, they must consider the warehouse capacity and capital availability. This paper constructs two probabilistic multi-item inventory models, considering discounts, expiration, warehouse capacity, and capital constraint. The first model considers all-unit discounts, while the second deals with incremental discounts. We consider three items to be managed and examine three replenishment policies, namely individual order, joint order, and a combined policy of individual and joint order, to minimize the total inventory cost. Sensitivity analysis is performed on the joint order policy to determine the influence of parameter values' changes on the reorder time and total inventory cost.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12759capital constraintdiscountinventory modelmulti-itemwarehouse capacity |
| spellingShingle | Claresta Tirta Saputera Gunawan Dharma Lesmono Daniel Salim MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTS Barekeng capital constraint discount inventory model multi-item warehouse capacity |
| title | MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTS |
| title_full | MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTS |
| title_fullStr | MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTS |
| title_full_unstemmed | MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTS |
| title_short | MULTI-ITEM PROBABILISTIC INVENTORY MODELS CONSIDERING DISCOUNT, EXPIRATION, WAREHOUSE CAPACITY, AND CAPITAL CONSTRAINTS |
| title_sort | multi item probabilistic inventory models considering discount expiration warehouse capacity and capital constraints |
| topic | capital constraint discount inventory model multi-item warehouse capacity |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/12759 |
| work_keys_str_mv | AT clarestatirtasaputeragunawan multiitemprobabilisticinventorymodelsconsideringdiscountexpirationwarehousecapacityandcapitalconstraints AT dharmalesmono multiitemprobabilisticinventorymodelsconsideringdiscountexpirationwarehousecapacityandcapitalconstraints AT danielsalim multiitemprobabilisticinventorymodelsconsideringdiscountexpirationwarehousecapacityandcapitalconstraints |