@inproceedings{03d6f686e9244aa6bc603f20ff112d2e,
title = "Solving Colored Traveling Salesman Problem via Multi-neighborhood Simulated Annealing Search",
abstract = "A colored traveling salesman problem (CTSP) is an important variant of the well-known multiple traveling salesman problem, which uses colors to differentiate salesmen's accessibility to individual cities to be visited. As a highly useful model for some complex scheduling problems, CTSP is NP-hard. A Multi-neighborhood Simulated Annealing Search (MSAS) approach is proposed to solve it in this paper. Starting from an initial solution, it iterates through two complementary neighborhoods: intra-route and inter-route neighborhoods. Experiments on three groups of 60 widely-used benchmark instances show that it achieves highly competitive performance compared to state-of-the-art algorithms. Moreover, MSAS can be integrated into other search methods to further improve performance, which is demonstrated by using a recently proposed iterated two-phase local search.",
keywords = "Colored traveling salesman problem, Heuristic search, Intelligent transportation, Local search, Simulated annealing",
author = "Yangming Zhou and Wenqiang Xu and Fu, {Zhang Hua} and Mengchu Zhou",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 18th IEEE International Conference on Networking, Sensing and Control, ICNSC 2021 ; Conference date: 03-12-2021 Through 05-12-2021",
year = "2021",
doi = "10.1109/ICNSC52481.2021.9702262",
language = "English (US)",
series = "ICNSC 2021 - 18th IEEE International Conference on Networking, Sensing and Control: Industry 4.0 and AI",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICNSC 2021 - 18th IEEE International Conference on Networking, Sensing and Control",
address = "United States",
}