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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 1151–1200 of 1277 papers

TitleStatusHype
Implementation of digital MemComputing using standard electronic componentsCode0
A Survey and Analysis of Evolutionary Operators for PermutationsCode0
Simulation Based Bayesian OptimizationCode0
How to Evaluate Machine Learning Approaches for Combinatorial Optimization: Application to the Travelling Salesman ProblemCode0
MGNN: Graph Neural Networks Inspired by Distance Geometry ProblemCode0
Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial OptimizationCode0
Graph-SCP: Accelerating Set Cover Problems with Graph Neural NetworksCode0
Black-box Combinatorial Optimization using Models with Integer-valued MinimaCode0
Curriculum Learning for Cumulative Return MaximizationCode0
Graph Coloring via Neural Networks for Haplotype Assembly and Viral Quasispecies ReconstructionCode0
Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial OptimizationCode0
Graph Adversarial Immunization for Certifiable RobustnessCode0
Global Optimal Path-Based Clustering AlgorithmCode0
Genetic Algorithm with Innovative Chromosome Patterns in the Breeding ProcessCode0
Revisiting Robust Model Fitting Using Truncated LossCode0
On Training-Test (Mis)alignment in Unsupervised Combinatorial Optimization: Observation, Empirical Exploration, and AnalysisCode0
Dynamic Programming on a Quantum Annealer: Solving the RBC ModelCode0
Leveraging Large Language Models to Develop Heuristics for Emerging Optimization ProblemsCode0
Word-level Textual Adversarial Attacking as Combinatorial OptimizationCode0
Dynamic Learning of Sequential Choice Bandit Problem under Marketing FatigueCode0
Reinforcement Learning for Solving the Vehicle Routing ProblemCode0
DistrictNet: Decision-aware learning for geographical districtingCode0
Optimal Intermittent Particle FilterCode0
Generalization of Machine Learning for Problem Reduction: A Case Study on Travelling Salesman ProblemsCode0
LLMs for Cold-Start Cutting Plane Separator ConfigurationCode0
Understanding Curriculum Learning in Policy Optimization for Online Combinatorial OptimizationCode0
Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based SamplingCode0
Local Energy Distribution Based Hyperparameter Determination for Stochastic Simulated AnnealingCode0
Optimization by Simulated AnnealingCode0
A random-key GRASP for combinatorial optimizationCode0
Too Big, so Fail? -- Enabling Neural Construction Methods to Solve Large-Scale Routing ProblemsCode0
Futureproof Static Memory PlanningCode0
Smart Predict-and-Optimize for Hard Combinatorial Optimization ProblemsCode0
Coupled Input-Output Dimension Reduction: Application to Goal-oriented Bayesian Experimental Design and Global Sensitivity AnalysisCode0
Artificial Potential Field-Based Path Planning for Cluttered EnvironmentsCode0
Synthesizing Interpretable Control Policies through Large Language Model Guided SearchCode0
A Graph Neural Network-Based QUBO-Formulated Hamiltonian-Inspired Loss Function for Combinatorial Optimization using Reinforcement LearningCode0
OsmLocator: locating overlapping scatter marks with a non-training generative perspectiveCode0
Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial OptimizationCode0
Approximation Algorithms for Combinatorial Optimization with PredictionsCode0
BinarizedAttack: Structural Poisoning Attacks to Graph-based Anomaly DetectionCode0
An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut ProblemCode0
Ants can orienteer a thief in their robberyCode0
Co-training for Policy LearningCode0
Distributional MIPLIB: a Multi-Domain Library for Advancing ML-Guided MILP MethodsCode0
Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set MatchingCode0
Formulating Neural Sentence Ordering as the Asymmetric Traveling Salesman ProblemCode0
Contrastive Losses and Solution Caching for Predict-and-OptimizeCode0
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial OptimizationCode0
Partial information decomposition: redundancy as information bottleneckCode0
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