Optimization of Transportation Costs in a Multi-Plant Distribution Network: A Linear Programming Approach for the Nigerian Bottling Company

Published2026-06-25IssueVol. 4 No. 2 (2026): International Journal of Applied and Natural SciencesPages17-30SectionResearch Article
DOI 10.61424/ijans.v4i2.918
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Abstract

Transportation is one of the largest controllable expenses in the distribution of fast-moving consumer goods. This research aims to minimize transportation costs in the Southeast and South-South region distribution network of the Nigerian Bottling Company (NBC), based on real data from 2014 to 2019. The four-plant, five-depot network has a total capacity of 5,760 truckloads to meet a demand of 5,328 truckloads. An analytical nonlinear programming model for route efficiencies and cost drivers, as well as plant-depot allocations under supply/demand constraints, was developed within a structured optimization framework. The findings indicate that the six-year baseline transportation cost of ₦284,089.68 was minimized to ₦9,633.64 after optimization, leading to a 96.6% reduction in cost and a profit of ₦274, 456. Maintenance and fuel consumption costs constituted 39.20% and 20.50% of the total baseline cost, respectively. Sensitivity analysis (±20% fuel) validates robustness (95.9 - 97.3% of savings retained) and cost-distance correlation (r = 0.8411) emphasizes the impact of infrastructure. The study leads to the conclusion that integrating transportation cost optimization with supply chain cost reduction can be required considerably.

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Keywords

  • Linear Programming, Transportation cost optimization, Supply chain management, Distribution network, Cost efficiency, Nigerian Bottling Company, Logistics optimization
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How to Cite

Silas U. Etiti, Kennedy C. Owuama, Swift O.N.K. Onyegirim, Ifeanyichukwu U. Onyenanu. (2026). Optimization of Transportation Costs in a Multi-Plant Distribution Network: A Linear Programming Approach for the Nigerian Bottling Company. International Journal of Applied and Natural Sciences, Vol. 4 No. 2 (2026): International Journal of Applied and Natural Sciences, 17-30. https://doi.org/10.61424/ijans.v4i2.918

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