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Journals / Journal of Transportation and Logistics / 2026 / Volume: 8 Issue: 1

Fleet Size and Mix Vehicle Routing Problem (FSMVRP), Adapted Large Neighbourhood Search Heuristic Optimization ProposalWith a Plant-capacity and Multi-day Planning Algorithm: A Livestock Feed Industry Case Study

Alperen Ekrem Çelikdin0000-0002-2215-3812
Pages
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Publication Date
2023-08-10
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The data set of the real-life problem that was used was applied to those three methods, and 0.45%, 0.81%, and 1.39% improvements were achieved using the methods, respectively.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The vehicle routing problem (VRP) is of great importance for feed factories that do not work with the dealership system.
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Key Findings & Data:Data used in the study came from the order data of a feed mill which operates in Turkey.
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Conclusion & Impact:The data set of the real-life problem that was used was applied to those three methods, and 0.45%, 0.81%, and 1.39% improvements were achieved using the methods, respectively.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Vehicle routing problem · fleet size mix with time windows · multi-day planning

Abstract

The vehicle routing problem (VRP) is of great importance for feed factories that do not work with the dealership system. This is especially important in the Central Anatolian region, where customers’ number of animals is low. Data used in the study came from the order data of a feed mill which operates in Turkey. Before selecting the most suitable VRP software vendor, the logistics manager of the plant was urged to analyse the results with the scope of percent fleet capacity used, service level (on-time deliveries), and total transportation cost incurred. As a requirement of the enterprise strategy, a multi-day planning algorithm was developed to level the daily production capacity of the factory while maintaining minimum transportation costs and maximum service level. It has been determined that better results are achieved with the developed multi-day planning algorithm for both methods of Simulated Annealing (SA), Genetic Algorithm (GA), and our Adapted Large Neighbourhood Search (ALNS) heuristic. The data set of the real-life problem that was used was applied to those three methods, and 0.45%, 0.81%, and 1.39% improvements were achieved using the methods, respectively.

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Cite This Article

Çelikdin, A. E., *, A. E. Ç. (2023). Fleet Size and Mix Vehicle Routing Problem (FSMVRP), Adapted Large Neighbourhood Search Heuristic Optimization ProposalWith a Plant-capacity and Multi-day Planning Algorithm: A Livestock Feed Industry Case Study. Journal of Transportation and Logistics, Volume: 8 Issue: 1. https://doi.org/10.26650/JTL.2023.1101161

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