Algorithms and Approaches for the Vehicle Routing Problem with Pickup and Delivery (VRPPD): A Survey

This systematic literature review (SLR) investigates recent advancements and trends in Vehicle Routing Problem with Pickup and Delivery (VRPPD), a crucial area in operations research and logistics. VRPPD optimization impacts operational costs, service quality, and environmental sustainability, especially with the growing demand from ecommerce. This review aims to address gaps in current literature, particularly focusing on real-time data integration, weather-related constraints, vehicle capacity, and sustainability. Utilizing the PRISMA methodology, 72 peer-reviewed articles from Scopus-indexed journals (2014-2024) were analyzed. The findings reveal significant progress in hybrid and metaheuristic algorithms, which combine multiple techniques to handle constraints like time windows, route efficiency, and fleet utilization. Despite these advancements, limited attention has been given to integrating weather data and dynamic constraints. The survey also highlights the need for more sustainable and real-time adaptive algorithms. Future research should explore multi-objective optimization, AI integration, and quantum computing to improve the efficiency and scalability of VRPPD solutions, especially in dynamic and high-demand environments such as e-commerce and logistics.