Application of the Vendor Managed Inventory (VMI) Model Based on Total Distribution Cost Optimization

Main Article Content

Giovano Alberto
Alexander Jimmy

Abstract

This study develops an optimization-based Vendor-Managed Inventory (VMI) model to improve coordination between inventory and transportation decisions in an upstream automotive distribution network in West Java. The problem is formulated as a multi-period Inventory Routing Problem (IRP) and solved using AMPL with CPLEX. The model minimizes total logistics cost, including transportation and inventory holding costs. A benchmark comparison with the company’s existing decentralized replenishment policy is conducted. Results show that the proposed VMI model reduces total monthly logistics cost by 10.66%, from IDR 2.74 billion to IDR 2.44 billion. In addition, service performance improves significantly, with demand fulfilment increasing from 91.3% to 99.2% and stock-out occurrences eliminated. The findings highlight the importance of integrated decision-making in freight distribution systems and provide practical insights for transport capacity planning and inventory positioning.

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Article Details

How to Cite
Alberto, G., & Alexander Jimmy. (2026). Application of the Vendor Managed Inventory (VMI) Model Based on Total Distribution Cost Optimization. Maritime Park: Journal of Maritime Technology and Society, 252–258. Retrieved from https://journal.unhas.ac.id/index.php/maritimepark/article/view/49829
Section
Marine Transportation and Port Management
Author Biography

Giovano Alberto, Pusat Studi Rantai Pasok, Universitas Katolik Parahyangan, Indonesia

Giovano Alberto is a Lecturer in the Department of Industrial Engineering, Universitas Katolik Parahyangan, Indonesia. His research interests include supply chain optimization, inventory–transportation integration, logistics system modeling, and decision support for freight distribution systems. His recent work focuses on optimization-based coordination mechanisms and their implications for transport efficiency and infrastructure utilization.

Received 2026-02-06
Accepted 2026-06-04
Published 2026-06-21

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