Solving Heterogeneous USV Scheduling Problems by Problem-Specific Knowledge Based Meta-Heuristics wi...
Solving Heterogeneous USV Scheduling Problems by Problem-Specific Knowledge Based Meta-Heuristics with Q-Learning
About this item
Full title
Author / Creator
Ma, Zhenfang , Gao, Kaizhou , Yu, Hui and Wu, Naiqi
Publisher
Basel: MDPI AG
Journal title
Language
English
Formats
Publication information
Publisher
Basel: MDPI AG
Subjects
More information
Scope and Contents
Contents
This study focuses on the scheduling problem of heterogeneous unmanned surface vehicles (USVs) with obstacle avoidance pretreatment. The goal is to minimize the overall maximum completion time of USVs. First, we develop a mathematical model for the problem. Second, with obstacles, an A* algorithm is employed to generate a path between two points wh...
Alternative Titles
Full title
Solving Heterogeneous USV Scheduling Problems by Problem-Specific Knowledge Based Meta-Heuristics with Q-Learning
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_20f38781a95c44bdb883cd8205c33f87
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_20f38781a95c44bdb883cd8205c33f87
Other Identifiers
ISSN
2227-7390
E-ISSN
2227-7390
DOI
10.3390/math12020339
