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2002.05513
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Multi-Vehicle Routing Problems with Soft Time Windows: A Multi-Agent Reinforcement Learning Approach
Transportation Research Part C: Emerging Technologies (Transp. Res. Part C), 2020
13 February 2020
Kecheng Zhang
Meng Li
Zhengchao Zhang
Xi Lin
Fang He
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Papers citing
"Multi-Vehicle Routing Problems with Soft Time Windows: A Multi-Agent Reinforcement Learning Approach"
32 / 32 papers shown
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Multiobjective Vehicle Routing Optimization with Time Windows: A Hybrid Approach Using Deep Reinforcement Learning and NSGA-II
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Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with Perspectives
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A Deep Reinforcement Learning Approach for Solving the Traveling Salesman Problem with Drone
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Diaformer: Automatic Diagnosis via Symptoms Sequence Generation
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Multi-Agent Path Planning Using Deep Reinforcement Learning
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Deep Reinforcement Learning for Demand Driven Services in Logistics and Transportation Systems: A Survey
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254
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An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problem
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Solve routing problems with a residual edge-graph attention neural network
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Analytics and Machine Learning in Vehicle Routing Research
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Ruibin Bai
Xinan Chen
Zhi-Long Chen
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