Permutation Picture of Graph Combinatorial Optimization Problems

Fuente: arXiv
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Main Author: Min, Yimeng
Format: Preprint
Published: 2024
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author Min, Yimeng
author_facet Min, Yimeng
contents This paper proposes a framework that formulates a wide range of graph combinatorial optimization problems using permutation-based representations. These problems include the travelling salesman problem, maximum independent set, maximum cut, and various other related problems. This work potentially opens up new avenues for algorithm design in neural combinatorial optimization, bridging the gap between discrete and continuous optimization techniques.
format Preprint
id arxiv_https___arxiv_org_abs_2410_17111
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Permutation Picture of Graph Combinatorial Optimization Problems
Min, Yimeng
Artificial Intelligence
Machine Learning
This paper proposes a framework that formulates a wide range of graph combinatorial optimization problems using permutation-based representations. These problems include the travelling salesman problem, maximum independent set, maximum cut, and various other related problems. This work potentially opens up new avenues for algorithm design in neural combinatorial optimization, bridging the gap between discrete and continuous optimization techniques.
title Permutation Picture of Graph Combinatorial Optimization Problems
topic Artificial Intelligence
Machine Learning
url https://arxiv.org/abs/2410.17111