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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 12211230 of 1277 papers

TitleStatusHype
An interacting replica approach applied to the traveling salesman problem0
Single Document Summarization based on Nested Tree Structure0
Mathematical Programming Strategies for Solving the Minimum Common String Partition Problem0
A Genetic Algorithm for solving Quadratic Assignment Problem(QAP)0
D-Bees: A Novel Method Inspired by Bee Colony Optimization for Solving Word Sense Disambiguation0
Matroid Bandits: Fast Combinatorial Optimization with Learning0
NuMVC: An Efficient Local Search Algorithm for Minimum Vertex Cover0
Principled Graph Matching Algorithms for Integrating Multiple Data Sources0
Effective Features of Remote Sensing Image Classification Using Interactive Adaptive Thresholding Method0
Parallel Genetic Algorithm to Solve Traveling Salesman Problem on MapReduce Framework using Hadoop Cluster0
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