Mathematical programming model for cost-optimized and environmentally sustainable supply chain design

Abstract

Sustainability is becoming increasingly important as a topic in general supply chains and cold chains. This study addresses the critical need for an integrated and comprehensive approach to supply chain design that simultaneously maximizes cost efficiency and incorporates environmental sustainability, focusing specifically on cold chains. Prior research has identified a gap in existing studies, highlighting the absence of an overarching framework from the logistics providers’ perspective. Our novel mathematical programming model introduces a unique strategy that carefully balances environmental concerns and cost optimization, addressing the shortcomings found in previous works. By integrating variables related to distribution, transportation, and inventory management, the model aims to minimize overall expenses and environmental impact, specifically regarding energy consumption and carbon emissions. We formulate and solve the optimization problem through rigorous mathematical programming, offering a flexible solution applicable to various logistics scenarios. The results demonstrate a significant reduction in overall expenses and environmental effects, providing logistics providers with a powerful tool for informed decision-making and sustainable supply chain management. This research contributes to the evolving field of supply chain sustainability by presenting a practical and effective model for maximizing cost savings while promoting environmental responsibility. The study concludes with compelling statistics, revealing a noteworthy decrease in overall expenses by €25 128 146.73 (100.25%) and environmental impact by 17 359.39 (100.04%). The outcomes show a notable decrease in general expenses and environmental effects, giving logistics providers a strong instrument for wise choices and sustainable supply chain management.