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@article{209686,
        author = {Arav Gupta and Aryan Agarwal and Arnav Shah and Arjun Narula},
        title = {Optimising the Domestic Distribution of Packaged Tea in India: A Transportation Problem Approach to Reducing FMCG Supply Chain Costs and Emissions},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {5},
        pages = {2947-2960},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=209686},
        abstract = {Background. Freight is one of the largest controllable costs in the supply chains of fast-moving consumer goods (FMCG) companies, and in India most of it moves by road. Packaged tea is a clear example. It is one of the most widely consumed FMCG categories, yet more than 80% of the crop is grown in the north-east and North Bengal, while consumption is concentrated in the north and west of the country. This paper asks how much of the cost of moving tea from gardens to consumers could be avoided by allocating supply to markets optimally, and what the answer implies for FMCG distribution planning.
Methods. The problem is formulated as a classical transportation problem with 9 producing regions and 27 consuming states and union territories. Supplies are the Tea Board’s 2023 regional production less region-wise exports. Demands are the Tea Board’s 2023 estimates of state-wise consumption. Route costs combine OpenStreetMap road distances with the directional zonal freight rates per tonne-kilometre estimated by NCAER for the Department for Promotion of Industry and Internal Trade (DPIIT). The problem is solved with the north-west corner, least-cost and Vogel’s approximation methods, improved to optimality with the modified distribution (MODI) method, and verified by linear programming. The plan is compared with a pooled proportional-sourcing benchmark that represents national blending. Extensions examine dual prices, unbalanced supply, alternative tariff structures, road–rail multimodal transport, sourcing-diversification constraints and the 2024 crop shortfall.
Results. The optimal plan costs INR 512.6 crore a year, or INR 4.41 per kg, against INR 630.5 crore (INR 5.43 per kg) under pooled sourcing. This is a saving of INR 117.9 crore (18.7%), with 16.9% fewer tonne-kilometres and 27.9 thousand tonnes less CO_2e. Vogel’s method comes within 5.3% of the optimum, against 6.6% for the least-cost method and 13.4% for the north-west corner rule. From Vogel’s starting solution, MODI needs only 16 iterations to reach the optimum. The dual prices show that South Indian tea is worth INR 3.8–5.0 per kg more than Assam tea at the margin. Under shortages the western markets are the first left short. Allowing rail for long hauls reduces cost by a further 23.6% and emissions by 58.8%. Limiting any single origin to 60% of a market’s supply raises cost by only 2.6%.
Conclusions. A textbook operations research model, built entirely from official data, identifies large and robust savings for an FMCG category with a sharply separated geography of production and consumption. The results show which origins should serve which markets, what each origin is worth, and how much resilience and modal shift would cost or save.},
        keywords = {transportation problem; FMCG; supply chain optimization; Vogel’s approximation method; MODI method; linear programming; tea; India; logistics cost},
        month = {October},
        }