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Combinatorial Optimization

Combinatorial Optimization is a category of problems which requires optimizing a function over a combination of discrete objects and the solutions are constrained. Examples include finding shortest paths in a graph, maximizing value in the Knapsack problem and finding boolean settings that satisfy a set of constraints. Many of these problems are NP-Hard, which means that no polynomial time solution can be developed for them. Instead, we can only produce approximations in polynomial time that are guaranteed to be some factor worse than the true optimal solution.

Source: Recent Advances in Neural Program Synthesis

Papers

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Showing 51–100 of 1277 papers

TitleStatusHype
Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot GeneralizationCode1
Moco: A Learnable Meta Optimizer for Combinatorial OptimizationCode1
Variational Annealing on Graphs for Combinatorial OptimizationCode1
Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization RegimeCode1
Combinatorial Optimization with Policy Adaptation using Latent Space SearchCode1
Large Language Models as Evolutionary OptimizersCode1
Neural Multi-Objective Combinatorial Optimization with Diversity EnhancementCode1
Survival of the Most Influential Prompts: Efficient Black-Box Prompt Search via Clustering and PruningCode1
Exploring the Power of Graph Neural Networks in Solving Linear Optimization ProblemsCode1
Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale GeneralizationCode1
A Deep Instance Generative Framework for MILP Solvers Under Limited Data AvailabilityCode1
Are Graph Neural Networks Optimal Approximation Algorithms?Code1
DeepACO: Neural-enhanced Ant Systems for Combinatorial OptimizationCode1
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNetsCode1
Let the Flows Tell: Solving Graph Combinatorial Problems with GFlowNetsCode1
Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local PolicyCode1
Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural NetworksCode1
Job Shop Scheduling via Deep Reinforcement Learning: a Sequence to Sequence approachCode1
Reinforcement Learning-based Non-Autoregressive Solver for Traveling Salesman ProblemsCode1
JoinGym: An Efficient Query Optimization Environment for Reinforcement LearningCode1
A Fast Task Offloading Optimization Framework for IRS-Assisted Multi-Access Edge Computing SystemCode1
Monte Carlo Policy Gradient Method for Binary OptimizationCode1
Automatic Truss Design with Reinforcement LearningCode1
D2Match: Leveraging Deep Learning and Degeneracy for Subgraph MatchingCode1
An End-to-End Reinforcement Learning Approach for Job-Shop Scheduling Problems Based on Constraint ProgrammingCode1
Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial OptimizationCode1
Discovering Dynamic Causal Space for DAG Structure LearningCode1
Towards Omni-generalizable Neural Methods for Vehicle Routing ProblemsCode1
DHRL-FNMR: An Intelligent Multicast Routing Approach Based on Deep Hierarchical Reinforcement Learning in SDNCode1
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNetsCode1
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time WindowsCode1
Quantum approximate optimization via learning-based adaptive optimizationCode1
RLOR: A Flexible Framework of Deep Reinforcement Learning for Operation ResearchCode1
Neural Airport Ground HandlingCode1
DAG Matters! GFlowNets Enhanced Explainer For Graph Neural NetworksCode1
ASP: Learn a Universal Neural Solver!Code1
Learning Large Neighborhood Search for Vehicle Routing in Airport Ground HandlingCode1
Quantum HyperNetworks: Training Binary Neural Networks in Quantum SuperpositionCode1
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial OptimizationCode1
Reinforced Genetic Algorithm for Structure-based Drug DesignCode1
Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial OptimizationCode1
Optimal Discrete Beamforming of RIS-Aided Wireless Communications: An Inner Product Maximization ApproachCode1
Online Control of Adaptive Large Neighborhood Search using Deep Reinforcement LearningCode1
ToupleGDD: A Fine-Designed Solution of Influence Maximization by Deep Reinforcement LearningCode1
Theory and Approximate Solvers for Branched Optimal Transport with Multiple SourcesCode1
DIMES: A Differentiable Meta Solver for Combinatorial Optimization ProblemsCode1
Winner Takes It All: Training Performant RL Populations for Combinatorial OptimizationCode1
Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems like Max-CutCode1
Learning with Combinatorial Optimization Layers: a Probabilistic ApproachCode1
Unsupervised Learning for Combinatorial Optimization with Principled Objective RelaxationCode1
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