arXiv:2410.17111cs.AIcs.LG2024-10
用排列编码统一建模多种图优化问题，为神经组合优化提供新思路。
Permutation Picture of Graph Combinatorial Optimization Problems
- 用排列表示解空间，统一建模多种图组合优化问题。
- 打通离散与连续优化的桥梁，支持更灵活的算法设计。
- 适合研究组合优化与神经算法交叉的学者参考。
本文提出一种基于排列表示的框架，用于建模广泛的图组合优化问题，包括旅行商问题、最大独立集、最大割及其他相关问题。该方法为神经组合优化中的算法设计开辟了新途径，弥合了离散优化与连续优化技术之间的鸿沟。
原文摘要 · Abstract (English)
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.
图优化排列编码神经优化
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