Frequency-based multi-agent patrolling model and its area partitioning solution method for balanced workload

Vourchteang Sea, Ayumi Sugiyama, Toshiharu Sugawara

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Multi-agent patrolling problem has received growing attention from many researchers due to its wide range of potential applications. In realistic environment, e.g., security patrolling, each location has different visitation requirement according to the required security level. Therefore, a patrolling system with non-uniform visiting frequency is preferable. The difference in visiting frequency generally causes imbalanced workload amongst agents leading to inefficiency. This paper, thus, aims at partitioning a given area to balance agents’ workload by considering that different visiting frequency and then generating route inside each sub-area. We formulate the problem of frequency-based multi-agent patrolling and propose its semi-optimal solution method, whose overall process consists of two steps – graph partitioning and sub-graph patrolling. Our work improve traditional k-means clustering algorithm by formulating a new objective function and combine it with simulated annealing – a useful tool for operations research. Experimental results illustrated the effectiveness and reasonable computational efficiency of our approach.

    Original languageEnglish
    Title of host publicationIntegration of Constraint Programming, Artificial Intelligence, and Operations Research - 15th International Conference, CPAIOR 2018, Proceedings
    PublisherSpringer-Verlag
    Pages530-545
    Number of pages16
    ISBN (Print)9783319930305
    DOIs
    Publication statusPublished - 2018 Jan 1
    Event15th International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2018 - Delft, Netherlands
    Duration: 2018 Jun 262018 Jun 29

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume10848 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other15th International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2018
    CountryNetherlands
    CityDelft
    Period18/6/2618/6/29

    Fingerprint

    Multi-agent Model
    Workload
    Partitioning
    Operations research
    Computational efficiency
    Simulated annealing
    Clustering algorithms
    Graph Partitioning
    K-means Algorithm
    K-means Clustering
    Operations Research
    Simulated Annealing
    Computational Efficiency
    Clustering Algorithm
    Subgraph
    Objective function
    Optimal Solution
    Requirements
    Experimental Results
    Range of data

    Keywords

    • Balanced workload
    • Frequency-based patrolling
    • Graph partitioning
    • k-means based
    • Linear programming
    • Multi-agent systems
    • Simulated annealing

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

    Cite this

    Sea, V., Sugiyama, A., & Sugawara, T. (2018). Frequency-based multi-agent patrolling model and its area partitioning solution method for balanced workload. In Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 15th International Conference, CPAIOR 2018, Proceedings (pp. 530-545). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10848 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-319-93031-2_38

    Frequency-based multi-agent patrolling model and its area partitioning solution method for balanced workload. / Sea, Vourchteang; Sugiyama, Ayumi; Sugawara, Toshiharu.

    Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 15th International Conference, CPAIOR 2018, Proceedings. Springer-Verlag, 2018. p. 530-545 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10848 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Sea, V, Sugiyama, A & Sugawara, T 2018, Frequency-based multi-agent patrolling model and its area partitioning solution method for balanced workload. in Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 15th International Conference, CPAIOR 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10848 LNCS, Springer-Verlag, pp. 530-545, 15th International Conference on Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2018, Delft, Netherlands, 18/6/26. https://doi.org/10.1007/978-3-319-93031-2_38
    Sea V, Sugiyama A, Sugawara T. Frequency-based multi-agent patrolling model and its area partitioning solution method for balanced workload. In Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 15th International Conference, CPAIOR 2018, Proceedings. Springer-Verlag. 2018. p. 530-545. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-93031-2_38
    Sea, Vourchteang ; Sugiyama, Ayumi ; Sugawara, Toshiharu. / Frequency-based multi-agent patrolling model and its area partitioning solution method for balanced workload. Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 15th International Conference, CPAIOR 2018, Proceedings. Springer-Verlag, 2018. pp. 530-545 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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