A Hybrid Distribution Network Model for Cost, Quality and Distribution Optimization in Perishable Goods Supply Chains
DOI:
https://doi.org/10.56532/mjsat.v5i1.462Keywords:
Distribution Network, Perishable Commodities, Optimization, Supply Chain, SustainabilityAbstract
The entrenched role of syndicates and intermediaries in the perishable goods sector inflates prices through artificial scarcity and hoarding, creating significant affordability challenges. Addressing these issues is critical amid rising global demand for fresh produce, which is highly vulnerable to quality degradation due to Supply Chain (SC) inefficiencies and inadequate cold storage practices. Consequently, formulating an SC Distribution Network (SCDN) becomes imperative to optimize distribution planning, mitigate quality deterioration, and ensure the sustainability of the SC. This research proposes an advanced SCDN architecture by developing a mixed-integer linear programming (MILP) model tailored for multi-echelon scenarios. The model aims to minimize overall SC costs, reduce cold storage expenses, and preserve the freshness of perishable goods through an efficient and hybrid distribution channel. The proposed model integrates competing objectives by addressing a multi-criteria problem via the weighted sum method (WSM) and is executed using the GUROBI optimizer in Python. Two case studies centred on the distribution of Mango and Jack fruits in Bangladesh validate the model's practicality. The findings highlight the strategic importance of optimal distribution center placement and a dual supply strategy, with plants meeting 63% of mango and 53% of jackfruit demand, reducing reliance on intermediaries by advocating direct shipping to markets while bypassing cold storage. This study further highlights the model's robustness and offers critical managerial insights, facilitating informed decision-making in the complex landscape of perishable product supply chains.
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