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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 601–625 of 1277 papers

TitleStatusHype
Reply to: Inability of a graph neural network heuristic to outperform greedy algorithms in solving combinatorial optimization problems—0
Reply to: Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set—0
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning—0
Differentiating Through Integer Linear Programs with Quadratic Regularization and Davis-Yin SplittingCode0
DeciLS-PBO: an Effective Local Search Method for Pseudo-Boolean OptimizationCode0
Learning To Dive In Branch And Bound—0
Two-Stage Learning For the Flexible Job Shop Scheduling Problem—0
Flex-Net: A Graph Neural Network Approach to Resource Management in Flexible Duplex NetworksCode0
Self-averaging of digital memcomputing machinesCode0
Efficient correlation-based discretization of continuous variables for annealing machines—0
A Combinatorial Semi-Bandit Approach to Charging Station Selection for Electric Vehicles—0
Unsupervised Learning for Combinatorial Optimization Needs Meta-LearningCode0
Mathematical Models and Reinforcement Learning based Evolutionary Algorithm Framework for Satellite Scheduling Problem—0
PA-GM: Position-Aware Learning of Embedding Networks for Deep Graph Matching—0
A machine learning framework for neighbor generation in metaheuristic search—0
A Local Optima Network View of Real Function Fitness Landscapes—0
Local Branching Relaxation Heuristics for Integer Linear Programs—0
Learning to repeatedly solve routing problems—0
Security Defense of Large Scale Networks Under False Data Injection Attacks: An Attack Detection Scheduling Approach—0
Walkability Optimization: Formulations, Algorithms, and a Case Study of TorontoCode0
Efficient Optimization with Higher-Order Ising Machines—0
Multi-Objective Linear Ensembles for Robust and Sparse Training of Few-Bit Neural NetworksCode0
Reinforcement Learning for Multi-Truck Vehicle Routing Problems—0
Fast Hyperparameter Tuning for Ising Machines—0
Synthetic Principal Component Design: Fast Covariate Balancing with Synthetic Controls—0
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