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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

Showing 201210 of 1277 papers

TitleStatusHype
A Compositional Algorithm for the Conflict-Free Electric Vehicle Routing Problem0
Ant Colony Optimization and Hypergraph Covering Problems0
Combinatorial Network Optimization with Unknown Variables: Multi-Armed Bandits with Linear Rewards0
Combinatorial optimization and reasoning with graph neural networks0
An SMT Based Compositional Algorithm to Solve a Conflict-Free Electric Vehicle Routing Problem0
An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problem0
A Generative Graph Method to Solve the Travelling Salesman Problem0
A General Large Neighborhood Search Framework for Solving Integer Linear Programs0
A Novel Differentiable Loss Function for Unsupervised Graph Neural Networks in Graph Partitioning0
A Comparison of Greedy and Optimal Assessment of Natural Language Student Input Using Word-to-Word Similarity Metrics0
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