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.
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Lei et al. (2024) studied this question.
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