A Memetic Algorithm for Vehicle Routing With Simultaneous Pickup and Delivery and Time Windows

The vehicle routing problem with simultaneous pickup and delivery and time windows (VRPSPDTW) has a number of real-world applications, especially in reverse logistics. In this work, we propose an effective memetic algorithm that integrates a lightweight feasible and infeasible route descent search and a learning-based adaptive route-inheritance crossover to solve this complex problem. We evaluate the effectiveness of the proposed algorithm on the set of 65 popular benchmark instances as well as 20 real-world large-scale benchmark instances. We provide a comprehensive analysis to better understand the design and performance of the proposed algorithm.