Istrazivanja i projektovanja za privreduJournal of Applied Engineering Science

COLLABORATIVE VENDOR MANAGED INVENTORY MODEL BY USING MULTI AGENT SYSTEM AND CONTINUOUS REVIEW (R, Q) REPLENISHMENT POLICY


DOI: 10.5937/jaes0-31532 
This is an open access article distributed under the CC BY 4.0
Creative Commons License

Volume 20 article 927 pages: 254-263

Purba Daru Kusuma*
Computer Engineering, Telkom University, Bandung, Indonesia

Meta Kallista
Computer Engineering, Telkom University, Bandung, Indonesia

In the vendor-managed inventory (VMI) system, the vendor takes over responsibility for managing customer inventory so that delivery is not based on the order but the customer’s inventory condition. It makes the vendor becomes a dominant entity, and customers are supplied by its own vendor exclusively. That is why most studies in VMI implement a single-vendor-single-customer or single-vendor-multi-customer scenario. In certain conditions, this exclusiveness can increase lost sales. Besides, most of them implement a single product scenario. In this work, we develop VMI model for the multi-vendor-customer-product scenario. This model is developed based on the collaborative multi-agent system. The relationship between vendors and customers is many-to-many. This work aims to reduce lost sales and maintain efficiency in the inventory. The continuous review (r, Q) policy is used as the replenishment model. The simulation result shows that the collaborative model creates higher sales, lower lost sales, and competitive inventory than the non-collaborative one. The lost sales is 50 to 75 percent lower. The sales percentage is 17 to 27 percent higher. The total retailers’ stock is 20 to 38 percent higher. The total vendors’ stock is 11 to 30 percent lower. The total stock in the supply chain in the collaborative model is 2 to 16 percent higher. The number of retailers is directly proportional to the total vendor’s stock and total supply chain stock gaps; inversely proportional to the lost sales gap; and not related to the sales percentage and total retailers’ stock gaps.

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