Papers

• Treedqn: Learning To Minimize Branch-and-bound Tree (2023)
  Dmitry Sorokin, Alexander Kostin
  2.26
• HyP-ASO: A Hybrid Policy-based Adaptive Search Optimization Framework for Large-Scale Integer Linear Programs (2025)
  Ning Xu et al.
  1.44
• Lower Bound on Howard Policy Iteration for Deterministic Markov Decision Processes (2025)
  Ali Asadi et al.
  1.28
• Solving the Job Shop Scheduling Problem with Graph Neural Networks: A Customizable Reinforcement Learning Environment (2025)
  Pablo Ari\~no Fern\'andez
  1.28
• CayleyPy RL: Pathfinding and Reinforcement Learning on Cayley Graphs (2025)
  A. Chervov et al.
  1.06
• Stochastic Runtime Analysis of a Cross Entropy Algorithm for Traveling Salesman Problems (2016)
  Zijun Wu et al.
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• Algorithms and Conditional Lower Bounds for Planning Problems (2018)
  Krishnendu Chatterjee et al.
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• An Optimal Control Framework for Online Job Scheduling with General Cost Functions (2019)
  S. Rasoul Etesami
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• Probability Learning based Tabu Search for the Budgeted Maximum Coverage Problem (2020)
  Liwen Li et al.
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• Deep Reinforcement Learning for Combinatorial Optimization: Covering Salesman Problems (2021)
  Kaiwen Li et al.
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• Graph Partitioning and Sparse Matrix Ordering using Reinforcement Learning and Graph Neural Networks (2021)
  Alice Gatti et al.
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• Comparing Heuristics, Constraint Optimization, and Reinforcement Learning for an Industrial 2D Packing Problem (2021)
  Stefan B\"ohm et al.
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• Supervised Permutation Invariant Networks for Solving the CVRP with Bounded Fleet Size (2022)
  Daniela Thyssens et al.
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• Solving Dynamic Graph Problems with Multi-Attention Deep Reinforcement Learning (2022)
  Udesh Gunarathna et al.
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• A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks (2022)
  Ismail R. Alkhouri et al.
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• Hierarchical Constrained Stochastic Shortest Path Planning via Cost Budget Allocation (2022)
  Sungkweon Hong and Brian C. Williams
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• Sym-NCO: Leveraging Symmetricity for Neural Combinatorial Optimization (2022)
  Minsu Kim et al.
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• Learning Optimal Solutions via an LSTM-Optimization Framework (2022)
  Dogacan Yilmaz et al.
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• Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling (2022)
  Cong Zhang et al.
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• Two-Stage Learning For the Flexible Job Shop Scheduling Problem (2023)
  Wenbo Chen et al.
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• Limited Query Graph Connectivity Test (2023)
  Mingyu Guo et al.
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• Edge Generation Scheduling for DAG Tasks Using Deep Reinforcement Learning (2023)
  Binqi Sun et al.
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• Approximately Optimal Search on a Higher-dimensional Sliding Puzzle (2024)
  Nono SC Merleau et al.
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