Optimizing Routing Solutions for Simultaneous Pickup and Delivery with Occasional Drivers

This article presents an innovative approach to solving the Vehicle Routing Problem with Simultaneous Pickup and Delivery and Occasional Drivers (VRPSPDOD). This problem involves minimizing the cost of servicing customer pickup and/or delivery requests using limited-capacity regular vehicles and single-service occasional drivers. To tackle this complicated problem, we introduce a novel Greedy Randomized Adaptive Search Procedure (GRASP) algorithm. Our method is characterized by its dynamic adjustment of the restricted candidate list size and implementation of problem-specific local search moves, ensuring a highly flexible and adaptive search process. The proposed algorithm outperforms the existing state-of-the-art method and achieves the best-known solutions for ۲۳ out of ۳۲ benchmark instances. This represents a significant average improvement of ۱.۲۶۶% over best-known solutions, demonstrating the practical efficacy of our methodology. Our research paves the way for further advancements in the field and provides practical insights and solutions for real-world logistics and supply chain management challenges.

Keywords:

Greedy Randomized Adaptive Search Procedure , Occasional Driver , Optimization Algorithms , Simultaneous Pickup and Delivery , Vehicle Routing Problem