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23 August 2022 A two-layer heuristic optimization algorithm for large-scale vehicle routing problem with drones
Jiajing Tang, Shuaipeng Jia, Zhongyu Ma
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Proceedings Volume 12305, International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022); 1230512 (2022) https://doi.org/10.1117/12.2645488
Event: International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022), 2022, Hangzhou, China
Abstract
With the increasing application in real life, drones have received more and more attention in recent years. In particular, drones show great potential when it comes to solving the last-mile delivery problems. Large-scale vehicle routing problems with drones (LSVRPDs) are challenging because most real-world problems typically involve thousands of delivery nodes. In this article, we proposed a two-layer heuristic optimization algorithm called THOA to address them. In the upper layer, three local search operators are used to generate different routes, each of which consists of several nodes. In the lower layer, a Branch-and-Bound method with special constraint is suggested to optimize the routes obtained from the upper layer. The proposed THOA is compared with a simulated annealing algorithm in six scenarios with different number of nodes. The experimental results demonstrate the effectiveness and efficiency of THOA, especially in VRPDs with a large number of nodes.
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Jiajing Tang, Shuaipeng Jia, and Zhongyu Ma "A two-layer heuristic optimization algorithm for large-scale vehicle routing problem with drones", Proc. SPIE 12305, International Symposium on Artificial Intelligence Control and Application Technology (AICAT 2022), 1230512 (23 August 2022); https://doi.org/10.1117/12.2645488
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KEYWORDS
Optimization (mathematics)
Algorithms
Algorithm development
Mathematical modeling
Computer science
Unmanned aerial vehicles
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