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An optimization model for the downstream supply chain network, considering consolidated warehouses and the selection of transportation mode.

Authors :
Mishra, Anurag
Dutta, Pankaj
Gottipalli, Naveen
Source :
International Journal of Productivity & Performance Management; 2024, Vol. 73 Issue 3, p912-942, 31p
Publication Year :
2024

Abstract

Purpose: The supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses. Design/methodology/approach: The model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis. Findings: Total cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs. Research limitations/implications: The study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each. Originality/value: The issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17410401
Volume :
73
Issue :
3
Database :
Complementary Index
Journal :
International Journal of Productivity & Performance Management
Publication Type :
Academic Journal
Accession number :
175870495
Full Text :
https://doi.org/10.1108/IJPPM-05-2022-0231