Milk Run Strategy Optimization with AnyLogistix: Chemical Product Distribution in Indonesia

Subject Areas : Supply chain management and logistics

Adji Candra Kurniawan ¹ , Yelita Anggiane Iskandar ^{2 *} , Resista Vikaliana ³ , Rahmad Inca Liperda ⁴ , I. D. G. Yogindra Adipramana ⁵ , Theodora Rinda Hernawati ⁶ , Delinda Amarajaya ⁷ , Nanda Ruswandi ⁸

1 - Faculty of Industrial Engineering, Universitas Pertamina, Jl. Teuku Nyak Arief, South Jakarta, 12220, Indonesia
2 - Faculty of Industrial Engineering, Universitas Pertamina, Jl. Teuku Nyak Arief, South Jakarta, 12220, Indonesia
3 - Faculty of Industrial Engineering, Universitas Pertamina, Jl. Teuku Nyak Arief, South Jakarta, 12220, Indonesia
4 - Industrial Engineering Department, Faculty of Engineering, Universitas Andalas, Padang, 25175, Indonesia
5 - Faculty of Industrial Engineering, Universitas Pertamina, Jl. Teuku Nyak Arief, South Jakarta, 12220, Indonesia
6 - Faculty of Industrial Engineering, Universitas Pertamina, Jl. Teuku Nyak Arief, South Jakarta, 12220, Indonesia
7 - Faculty of Industrial Engineering, Universitas Pertamina, Jl. Teuku Nyak Arief, South Jakarta, 12220, Indonesia
8 - Faculty of Industrial Engineering, Universitas Pertamina, Jl. Teuku Nyak Arief, South Jakarta, 12220, Indonesia

Received: 2024-10-23 Accepted : 2025-02-05

Keywords: anyLogistix, Milk Run, Product Distribution, Transportation Cost, Transportation Optimization,

Abstract :

This study focuses on the optimization of transportation routes for the distribution of chemical products Product X in the Jabodetabek and Karawang areas using the Transportation Optimization (TO) module in AnyLogistix software. This study uses a trial-and-error approach on the parameter "maximum number of customers in one route" to find the most optimal scenario in terms of transportation costs and distance traveled. Four scenarios are generated with different maximum numbers of customers per route, ranging from 3 to 6 customers. The results show that scenario 3, with a maximum of 5 customers per route, produces the lowest total transportation cost of IDR 36,113,000 and a total distance traveled of 12,235 km. Scenario 4, with 6 customers per route, increases transportation costs to IDR 38,808,000 due to the increase in the number of direct shipments due to distance constraints. This study highlights the importance of balancing the number of direct shipments, customer grouping, and route optimization to achieve cost efficiency. This study suggests that companies consider the use of heterogeneous vehicles and sourcing policies involving additional facilities for further optimization. Additional simulations using the simulation module (SIM) in AnyLogistix are also proposed to simulate facility costs and transportation mode selection in more detail.

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