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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 101–150 of 1277 papers

TitleStatusHype
DIMES: A Differentiable Meta Solver for Combinatorial Optimization ProblemsCode1
Active Learning Meets Optimized Item SelectionCode1
DOGE-Train: Discrete Optimization on GPU with End-to-end TrainingCode1
Dynamic Partial Removal: A Neural Network Heuristic for Large Neighborhood SearchCode1
Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial OptimizationCode1
Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems like Max-CutCode1
A Fast Task Offloading Optimization Framework for IRS-Assisted Multi-Access Edge Computing SystemCode1
Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization SolversCode1
HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMsCode1
Efficient Active Search for Combinatorial Optimization ProblemsCode1
Exact Combinatorial Optimization with Graph Convolutional Neural NetworksCode1
BILP-Q: Quantum Coalition Structure GenerationCode1
Hybrid Genetic Search for the CVRP: Open-Source Implementation and SWAP* NeighborhoodCode1
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling ProblemsCode1
Equivariant quantum circuits for learning on weighted graphsCode1
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on GraphsCode1
Quantum approximate optimization via learning-based adaptive optimizationCode1
Neural Multi-Objective Combinatorial Optimization with Diversity EnhancementCode1
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on GraphsCode1
Incremental Sampling Without Replacement for Sequence ModelsCode1
Optimal Discrete Beamforming of RIS-Aided Wireless Communications: An Inner Product Maximization ApproachCode1
Parallel AutoRegressive Models for Multi-Agent Combinatorial OptimizationCode1
A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial OptimizationCode1
Exploring the Power of Graph Neural Networks in Solving Linear Optimization ProblemsCode1
Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization AlgorithmsCode1
Decision-Focused Learning: Through the Lens of Learning to RankCode1
Geometric Deep Reinforcement Learning for Dynamic DAG SchedulingCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionCode1
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics NetworkCode1
FusDreamer: Label-efficient Remote Sensing World Model for Multimodal Data ClassificationCode1
GOAL: A Generalist Combinatorial Optimization Agent LearningCode1
Attention, Learn to Solve Routing Problems!Code1
Automatic Truss Design with Reinforcement LearningCode1
Generative Adversarial Networks in Estimation of Distribution Algorithms for Combinatorial OptimizationCode1
A Two-stage Reinforcement Learning-based Approach for Multi-entity Task AllocationCode1
BQ-NCO: Bisimulation Quotienting for Efficient Neural Combinatorial OptimizationCode1
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming ProblemCode1
Belief Propagation Neural NetworksCode1
Are Graph Neural Networks Optimal Approximation Algorithms?Code1
A Reinforcement Learning Approach to the Orienteering Problem with Time WindowsCode1
A Reinforcement Learning Environment For Job-Shop SchedulingCode1
Hybrid Pointer Networks for Traveling Salesman Problems OptimizationCode1
FireCommander: An Interactive, Probabilistic Multi-agent Environment for Heterogeneous Robot TeamsCode1
CLIPPER: A Graph-Theoretic Framework for Robust Data AssociationCode1
A Word is Worth A Thousand Dollars: Adversarial Attack on Tweets Fools Stock PredictionsCode1
ASP: Learn a Universal Neural Solver!Code1
Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement LearningCode1
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time WindowsCode1
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
Feature Importance Ranking for Deep LearningCode1
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