zcaicaros Goto Github PK

dagnn

A graph neural network tailored to directed acyclic graphs that outperforms conventional GNNs by leveraging the partial order as strong inductive bias besides other suitable architectural features.

drl-mtsp

Reinplemtation of paper "A reinforcement learning approach for optimizing multiple traveling salesman problems over graphs"

grok-1

Grok open release

l2d

Official implementation of paper "Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning"

l2s

Official implementation of paper "Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling"

learning-d2d-task-off-loads

learning-reactive-rule-programs

manager-worker-mtsptwr

Official implementation of paper "Learning to Solve Multiple-TSP with Time Window and Rejections via Deep Reinforcement Learning"

neurols

Code repository for the corresponding paper "Learning to Control Local Search for Combinatorial Optimization"

rlgnn-jssp

A reimplementation of paper "Learning to schedule job-shop problems: representation and policy learning using graph neural network and reinforcement learning"

robot-compete

sc2002

schedulenet

A reimplement of paper "ScheduleNet: Learn to solve multi-agent scheduling problems with reinforcement learning "

tbgat

Official implementation of paper "Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem"

zcaicaros