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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 9911000 of 1277 papers

TitleStatusHype
Estimation of the yield curve for Costa Rica using combinatorial optimization metaheuristics applied to nonlinear regression0
Black-box Combinatorial Optimization using Models with Integer-valued MinimaCode0
Multi-objectivization Inspired Metaheuristics for the Sum-of-the-Parts Combinatorial Optimization Problems0
Multidataset Independent Subspace Analysis with Application to Multimodal FusionCode0
Self-Assignment Flows for Unsupervised Data Labeling on Graphs0
Learning to Order Graph Elements with Application to Multilingual Surface Realization0
Word-level Textual Adversarial Attacking as Combinatorial OptimizationCode0
Kernels of Mallows Models under the Hamming Distance for solving the Quadratic Assignment ProblemCode0
A Memetic Algorithm Based on Breakout Local Search for the Generalized Travelling Salesman Problem0
Entity Summarization: State of the Art and Future Challenges0
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