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Neural Combinatorial Optimization with Heavy Decoder-Toward Large Scale Generalization

NIPS23 重解码轻编码 + 迭代重构局部解改进

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization 重解码器的神经组合优化:面向大规模泛化 来自南方科技大学和香港城市大学 开源:https://github.com/CIAM-Group/NCO_code/tree/main/single_objective/L...

Let the Flows Tell Solving Graph Combinatorial Problems with GFlowNets

NIPS23 GFlowNets

NIPS23 Let the Flows Tell Solving Graph Combinatorial Problems with GFlowNets 用GFlowNets求解图组合优化问题 来自Mila实验室和Google DeepMind 开源:https://github.com/zdhNarsil/GFlowNet-CombOpt (没研究过相关内容,没看懂) 摘要 ...

双层规划问题

综述和一些应用

双层规划问题 \[\begin{aligned} \min_{(x,y)}\quad &f(x,y) \\ \mathrm{s.t.}\quad &g(x,y)\leqslant0\\ \quad &y\in S(x), \end{aligned}\] 其中 $S(x)$ 表示下层问题: \[\begin{aligned} \min_{y}\quad &a...

Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt

NIPS23 k-opt learn to imporve + mask优化不可行探索 + 双流解码器

Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt 用柔性神经k-Opt学习搜索路由问题的可行和不可行区域 开源:https://github.com/yining043/NeuOpt 摘要 在本文中,我们提出了神经k-Opt (NeuO...

DeepACO Neural-enhanced Ant Systems for Combinatorial Optimization

NIPS23 神经蚁群系统 构造+局部搜索 泛用的元启发式

DeepACO Neural-enhanced Ant Systems for Combinatorial Optimization DeepACO:用于组合优化的神经增强蚁群系统 代码:https://github.com/henry-yeh/DeepACO 摘要 蚁群优化算法是一种元启发式算法,已成功地应用于各种组合优化问题。传统上,针对特定问题定制蚁群算法需要知识驱动的启发...

Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift

NIPS23 集成学习提高泛化性

Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift 配送移位下基于集成的车辆路径问题深度强化学习 摘要 虽然在独立同分布情况下表现良好,但大多数现有的VRP神经方法在分布变化的情况下难以泛化。为了解决这个问题,我们提出了一种基于集成的vrp深...

Deep Reinforcement Learning for the Electric Vehicle Routing Problem With Time Windows

EVRPTW

Deep Reinforcement Learning for the Electric Vehicle Routing Problem With Time Windows 文章原文:https://ieeexplore.ieee.org/document/9520134 发表在2022 IEEE Transactions on Intelligent Transportation Sy...

Combinatorial Optimization with Policy Adaptation using Latent Space Search

NIPS23 潜在空间采样学习+推理时候搜索

NIPS23 Combinatorial Optimization with Policy Adaptation using Latent Space Search 基于潜在空间搜索的策略自适应组合优化 来自InstaDeep 代码和数据集: https://github.com/instadeepai/compass (我没读代码,理解的不是很透彻,没有附录感觉讲的也不是很清楚,需...

Winner Takes It All-Training Performant RL Populations for Combinatorial Optimization

NIPS23 多智能体(种群)学习

Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization 赢家通吃:训练用于组合优化的高性能RL种群 来自InstaDeep 摘要 将强化学习(RL)应用于组合优化问题是有吸引力的,因为它不需要专家知识或预先解决的实例。然而,由于其固有的复杂性,期望智能体在一次推理中解...

BQ-NCO Bisimulation Quotienting for Efficient Neural Combinatorial Optimization

NIPS23 新的马尔可夫决策过程表示并改进学习框架

BQ-NCO Bisimulation Quotienting for Efficient Neural Combinatorial Optimization BQ-NCO:高效神经组合优化的双模拟分法(Bisimulation Quotienting不知道中文怎么翻译) 来自Naver Labs Europe 代码:naver/bq-nco (github.com) 摘要 尽管基...