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05/31/2023
Towards Omni-generalizable Neural Methods for Vehicle Routing Problems
Learning heuristics for vehicle routing problems (VRPs) has gained much ...
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02/27/2023
Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling
Dispatching vehicle fleets to serve flights is a key task in airport gro...
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11/20/2022
Learning to Search for Job Shop Scheduling via Deep Reinforcement Learning
Recent studies in using deep reinforcement learning (DRL) to solve Job-s...
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09/13/2022
Learning to Solve Multiple-TSP with Time Window and Rejections via Deep Reinforcement Learning
We propose a manager-worker framework based on deep reinforcement learni...
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04/25/2022
Efficient Neural Neighborhood Search for Pickup and Delivery Problems
We present an efficient Neural Neighborhood Search (N2S) approach for pi...
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11/01/2021
Learning Large Neighborhood Search Policy for Integer Programming
We propose a deep reinforcement learning (RL) method to learn large neig...
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10/15/2021
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem
We present NeuroLKH, a novel algorithm that combines deep learning with ...
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10/06/2021
Heterogeneous Attentions for Solving Pickup and Delivery Problem via Deep Reinforcement Learning
Recently, there is an emerging trend to apply deep reinforcement learnin...
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10/06/2021
Deep Reinforcement Learning for Solving the Heterogeneous Capacitated Vehicle Routing Problem
Existing deep reinforcement learning (DRL) based methods for solving the...
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10/06/2021
Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer
Recently, Transformer has become a prevailing deep architecture for solv...
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06/30/2021
Dual Aspect Self-Attention based on Transformer for Remaining Useful Life Prediction
Remaining useful life prediction (RUL) is one of the key technologies of...
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12/19/2020
Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems
We present a novel deep reinforcement learning method to learn construct...
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10/23/2020
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
Priority dispatching rule (PDR) is widely used for solving real-world Jo...
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12/23/2019
Learning Variable Ordering Heuristics for Solving Constraint Satisfaction Problems
Backtracking search algorithms are often used to solve the Constraint Sa...
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12/12/2019
