An Algorithm Study for Modeling the Multi-Period Inventory Transportation Problem in Construction Industry (S/O 14585)
Vendor managed inventory (VMI) is an illustration of effective partnering and collaboration practices between upstream and downstream points in a supply chain. VMI policy is an integrating decision between a supplier and the customers in which the supplier takes the accountability of sustaining the...
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| Main Authors: | , |
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| Format: | Monograph |
| Language: | English |
| Published: |
UUM
2021
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/30212/1/14585.pdf https://repo.uum.edu.my/id/eprint/30212/ |
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| Institution: | Universiti Utara Malaysia |
| Language: | English |
| Summary: | Vendor managed inventory (VMI) is an illustration of effective partnering and collaboration practices between upstream and downstream points in a supply chain. VMI policy is an integrating decision between a supplier and the customers in which the supplier takes the accountability of sustaining the customers’ inventory while confirming that no stock-out. The supplier indicates when each delivery time takes place, so that the customers are no longer responses to the customers' orders. Under the VMI system, the planning is proactive as it is based on the available information rather than reactive to customers' orders. Consequently, in this research, we expected that the demand at the construction sites are constant and stationary, and the construction consolidation centre (CCC) is implementing a VMI system. The concentration of this research is to minimize the transportation and inventory holding costs of the customers for a two-stage supply chain system in the construction industry. The problem is to identify what is the delivery quantities to the construction sites, what is delivery times and which routes should be used to deliver products to the customers at the construction site for the single-period deterministic inventory routing problem (SP-DIRP) in the construction sector. Furthermore, realistic side-constraints such as driving time restrictions, storage capacities constraints and constant replacement intervals are considered. Results of a simplified real-life case implementing the proposed linear mixed-integer program are shown and discussed in detail. |
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