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Title: Hybrid Method by Integrating Deep Reinforcement Learning and Heuristics Approach for Capacitated Vehicle Routing Problem
Other Titles: Derin Pekiştirmeli Öğrenme ve Sezgisel Yöntemlerin Kapasite Kisitli Araç Rotalama Probleminde Entegre Kullanimi
Authors: Aktaş, Y.F.
Özbayoğlu, A.M.
Keywords: attention
Deep reinforcement learning
Deep learning
Heuristic methods
Learning systems
Reinforcement learning
Vehicle routing
Deep reinforcement learning
Hybrid method
Problem space
Reinforcement learning approach
Reinforcement learning models
Reinforcement learnings
Issue Date: 2022
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: With the spread of online platforms, problems such as manned/unmanned food delivery, cargo delivery, raw material delivery, are increasing the importance of logistics day by day. Vehicle routing problem, which is one of the most important problems in the field of logistics, is a combinatorial problem and as the problem space grows, it takes a long time to find a solution with human effort and in most cases it is not even possible. Thus, it becomes essential for the solution of this problem to be autonomous. Although it is possible to solve the problem with classical heuristic optimization methods, it takes a long time and sometimes does not give a good enough solution. Deep reinforcement learning models with attention mechanisms have great potential in this regard. However,in case of insufficient training in large problem space, it is possible to get away from the optimal solution. In this study, better results are taken in an acceptable time by using the deep reinforcement learning models with attention-model and heuristic methods in a hybrid way. © 2022 IEEE.
Description: 2022 Innovations in Intelligent Systems and Applications Conference, ASYU 2022 -- 7 September 2022 through 9 September 2022 -- 183936
ISBN: 9781665488945
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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