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Found 7 papers, 6 papers with code
Graph Neural Networks for Job Shop Scheduling Problems: A Survey
Job shop scheduling problems (JSSPs) represent a critical and challenging class of combinatorial optimization problems.
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
Learning to solve vehicle routing problems (VRPs) has garnered much attention.
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization Benchmark
To fill this gap, we introduce RL4CO, a unified and extensive benchmark with in-depth library coverage of 23 state-of-the-art methods and more than 20 CO problems.
Towards Omni-generalizable Neural Methods for Vehicle Routing Problems
Learning heuristics for vehicle routing problems (VRPs) has gained much attention due to the less reliance on hand-crafted rules.
Neural Airport Ground Handling
Airport ground handling (AGH) offers necessary operations to flights during their turnarounds and is of great importance to the efficiency of airport management and the economics of aviation.
Learning Large Neighborhood Search for Vehicle Routing in Airport Ground Handling
Dispatching vehicle fleets to serve flights is a key task in airport ground handling (AGH).
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks
Adversarial training (AT) with imperfect supervision is significant but receives limited attention.
