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Found 3 papers, 1 papers with code
PUSH: a primal heuristic based on Feasibility PUmp and SHifting
The main idea is to replace the rounding phase of the Feasibility Pump with a suitable adaptation of the Shifting and other rounding heuristics.
An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents
The aim is to build up a greedy-like heuristic able to learn on some distribution of JSSP instances, different in the number of jobs and machines.
Solving the single-track train scheduling problem via Deep Reinforcement Learning
In these cases, it is the duty of human traffic controllers, the so-called dispatchers, to do their best to minimize the impact on traffic.
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