OPTIMIZATION OF LAST-MILE DELIVERY IN KSA
DOI:
https://doi.org/10.55197/qjoest.v6i1.197Keywords:
last-mile delivery, e-commerce, Mathematical model, vehicle route, python programmingAbstract
The rapid growth of e-commerce in Saudi Arabia has intensified the need for efficient last-mile delivery solutions. This study investigates the optimization of last-mile delivery using a mathematical model and a Python-based approach to enhance efficiency, reduce costs, and improve customer satisfaction. A survey conducted among Saudi residents highlighted significant challenges, including delivery delays, high costs, and inefficient routing. The study developed a capacitated vehicle routing problem (CVRP) model, which aimed to minimize total travel distance while meeting customer demands within vehicle capacity constraints. The model, implemented using LINGO software, demonstrated a 17.21% reduction in travel distance, translating into cost and time savings. However, due to computational complexity, a Python-based optimization program was developed as an alternative, reducing the total distance traveled by 31.15% and cutting delivery time by 33.82%. The results indicate that automated route optimization significantly enhances last-mile logistics, ensuring timely deliveries and reducing operational expenses. The findings highlight the importance of integrating mathematical optimization with programming solutions to streamline logistics operations. This study offers practical insights for logistics companies in Saudi Arabia to adopt advanced route-planning technologies, ultimately improving service efficiency and customer experience. Future research should explore integrating real-time traffic data and customer preferences to further optimize last-mile delivery processes.
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