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Combining Meta-Heuristics and K-Means++ for Solving Unmanned Surface Vessels Task Assignment and Path Planning Problems

EasyChair Preprint 11231

6 pagesDate: November 2, 2023

Abstract

This study addresses Unmanned Surface Vessels (USVs) task assignment and path planning problems with minimizing the maximum completion time of USVs. First, a mathematical model is developed for the concerned problems. Second, an unsupervised learning algorithm, K-Means++, is employed to assign multi-tasks to USVs. According to the assignment results, five meta-heuristics are used to solve path planning problems for USVs. Finally, experiments are executed to solve 10 cases with different scales. The effectiveness of K-Means++ for task assignment is verified. The results of five meta-heuristics for path planning are reported and analyzed. The harmony search algorithm has the strongest competitiveness among all compared algorithms for solving the concerned problems.

Keyphrases: Meta-heuristics, Unmanned surface vessel, k-means++, path planning, task assignment

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:11231,
  author    = {Weiyu Tang and Kaizhou Gao and Minglong Gao and Zhenfang Ma},
  title     = {Combining Meta-Heuristics and K-Means++ for Solving Unmanned Surface Vessels Task Assignment and Path Planning Problems},
  howpublished = {EasyChair Preprint 11231},
  year      = {EasyChair, 2023}}
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