Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP-Reference-Cited by-同舟云学术

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Using Reinforcement Learning for Per-Instance Algorithm Configuration on the TSP

Published:2023-12-05 Issue: Volume:68 Page:361-368
ISSN:
Container-title:2023 IEEE Symposium Series on Computational Intelligence (SSCI)
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Author:

Vinzent Seiler Moritz¹,Rook Jeroen²,Heins Jonathan³,Ludger Preuß Oliver¹,Bossek Jakob⁴,Trautmann Heike¹

Affiliation:

1. University of Münster,Data Science: Statistics and Optimization,Münster,Germany

2. University of Twente,Data Management and Biometrics,Enschede,Netherlands

3. TU Dresden,Big Data Analytics in Transportation,Dresden,Germany

4. Aachen University,Chair for AI Methodology RWTH,Aachen,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10371778/10371788/10372008.pdf?arnumber=10372008

Reference36 articles.

1. Traveling Salesman Problem

2. A branch and bound algorithm for the travelling salesman and the transportation routing problems

3. A Powerful Genetic Algorithm Using Edge Assembly Crossover for the Traveling Salesman Problem

4. An effective implementation of the Lin–Kernighan traveling salesman heuristic

5. On the Empirical Scaling Behaviour of State-of-the-art Local Search Algorithms for the Euclidean TSP

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Dancing to the State of the Art?;Lecture Notes in Computer Science;2024

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