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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 1–50 of 1277 papers

TitleStatusHype
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization BenchmarkCode4
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-ExpertsCode3
ReEvo: Large Language Models as Hyper-Heuristics with Reflective EvolutionCode3
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language ModelCode3
HeurAgenix: Leveraging LLMs for Solving Complex Combinatorial Optimization ChallengesCode2
Solving the Job Shop Scheduling Problem with Graph Neural Networks: A Customizable Reinforcement Learning EnvironmentCode2
HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial OptimizationCode2
Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic DesignCode2
Efficient Parallel Genetic Algorithm for Perturbed Substructure Optimization in Complex NetworkCode2
LLMOPT: Learning to Define and Solve General Optimization Problems from ScratchCode2
UDC: A Unified Neural Divide-and-Conquer Framework for Large-Scale Combinatorial Optimization ProblemsCode2
Joint Admission Control and Resource Allocation of Virtual Network Embedding via Hierarchical Deep Reinforcement LearningCode2
Combinatorial Optimization with Automated Graph Neural NetworksCode2
A Diffusion Model Framework for Unsupervised Neural Combinatorial OptimizationCode2
Neural Combinatorial Optimization Algorithms for Solving Vehicle Routing Problems: A Comprehensive Survey with PerspectivesCode2
FloorSet -- a VLSI Floorplanning Dataset with Design Constraints of Real-World SoCsCode2
Ant Colony Sampling with GFlowNets for Combinatorial OptimizationCode2
Learning to Solve Job Shop Scheduling under UncertaintyCode2
Domain-Independent Dynamic ProgrammingCode2
DIFUSCO: Graph-based Diffusion Solvers for Combinatorial OptimizationCode2
Diffusion models as plug-and-play priorsCode2
DevFormer: A Symmetric Transformer for Context-Aware Device PlacementCode2
Revocable Deep Reinforcement Learning with Affinity Regularization for Outlier-Robust Graph MatchingCode2
Structured Reinforcement Learning for Combinatorial Decision-MakingCode1
A Comprehensive Evaluation of Contemporary ML-Based Solvers for Combinatorial OptimizationCode1
CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial OptimizationCode1
Neural Combinatorial Optimization for Real-World RoutingCode1
FusDreamer: Label-efficient Remote Sensing World Model for Multimodal Data ClassificationCode1
Starjob: Dataset for LLM-Driven Job Shop SchedulingCode1
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop SchedulingCode1
Combinatorial Optimization Perspective based Framework for Multi-behavior RecommendationCode1
Multi Agent Reinforcement Learning for Sequential Satellite Assignment ProblemsCode1
HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMsCode1
Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for Mixed-Integer Programming ProblemCode1
Neural Combinatorial Optimization for Stochastic Flexible Job Shop Scheduling ProblemsCode1
Beyond the Heatmap: A Rigorous Evaluation of Component Impact in MCTS-Based TSP SolversCode1
Towards Fairness and Privacy: A Novel Data Pre-processing Optimization Framework for Non-binary Protected AttributesCode1
Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural NetworksCode1
Parallel AutoRegressive Models for Multi-Agent Combinatorial OptimizationCode1
DataSculpt: Crafting Data Landscapes for Long-Context LLMs through Multi-Objective PartitioningCode1
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt TuningCode1
Take a Step and Reconsider: Sequence Decoding for Self-Improved Neural Combinatorial OptimizationCode1
A Two-stage Reinforcement Learning-based Approach for Multi-entity Task AllocationCode1
Memory-Enhanced Neural Solvers for Efficient Adaptation in Combinatorial OptimizationCode1
GOAL: A Generalist Combinatorial Optimization Agent LearningCode1
Learning Solution-Aware Transformers for Efficiently Solving Quadratic Assignment ProblemCode1
Tackling Prevalent Conditions in Unsupervised Combinatorial Optimization: Cardinality, Minimum, Covering, and MoreCode1
Self-Improvement for Neural Combinatorial Optimization: Sample without Replacement, but ImprovementCode1
RouteExplainer: An Explanation Framework for Vehicle Routing ProblemCode1
MMSR: Symbolic Regression is a Multi-Modal Information Fusion TaskCode1
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