Optimization of social security patrol strategy based on graph theory and GGC algorithm
Abstract To cope with complex dynamic patrol environments and maximize the benefits of regional social security patrols, this study abstracts patrol areas as a graph model and constructs a network diagram of the social security patrol area. Then, an initial configuration method for intelligent patro...
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| Format: | Article |
| Language: | English |
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Springer
2025-07-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-025-07386-3 |
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| author | Jian Wang |
| author_facet | Jian Wang |
| author_sort | Jian Wang |
| collection | DOAJ |
| description | Abstract To cope with complex dynamic patrol environments and maximize the benefits of regional social security patrols, this study abstracts patrol areas as a graph model and constructs a network diagram of the social security patrol area. Then, an initial configuration method for intelligent patrol agents based on greedy algorithms is proposed, and game theory was introduced to construct an "attacker defender" game patrol model. The policy set and payoff function are defined, and a generalized geometric coverage algorithm is designed to solve the policy set of both parties in the model, thereby obtaining the optimal patrol strategy for intelligent patrol agents. The results indicated that the initial configuration method of intelligent patrol agents based on greedy algorithm reduced the global average idle time of patrol agents to about 200 s and 765 s respectively for the initial deployment of road networks A and B. Under the same number of patrol agents, the global average coverage rate increased to over 80% faster. In addition, the revenue of the GGC algorithm based on multi-linear programming for solving the A and B game patrol models was (15.0, -30.0) and (21.1, -38.2), respectively, which were superior to other strategies. The above data indicates that the research method can improve patrol efficiency and comprehensive coverage, providing strong support for optimizing social security patrol strategies. |
| format | Article |
| id | doaj-art-6e9a2452b9cc48d7a7bef5261d59cae1 |
| institution | Kabale University |
| issn | 3004-9261 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-6e9a2452b9cc48d7a7bef5261d59cae12025-08-20T04:03:06ZengSpringerDiscover Applied Sciences3004-92612025-07-017711810.1007/s42452-025-07386-3Optimization of social security patrol strategy based on graph theory and GGC algorithmJian Wang0Public Order Administration Department, Liaoning Police CollegeAbstract To cope with complex dynamic patrol environments and maximize the benefits of regional social security patrols, this study abstracts patrol areas as a graph model and constructs a network diagram of the social security patrol area. Then, an initial configuration method for intelligent patrol agents based on greedy algorithms is proposed, and game theory was introduced to construct an "attacker defender" game patrol model. The policy set and payoff function are defined, and a generalized geometric coverage algorithm is designed to solve the policy set of both parties in the model, thereby obtaining the optimal patrol strategy for intelligent patrol agents. The results indicated that the initial configuration method of intelligent patrol agents based on greedy algorithm reduced the global average idle time of patrol agents to about 200 s and 765 s respectively for the initial deployment of road networks A and B. Under the same number of patrol agents, the global average coverage rate increased to over 80% faster. In addition, the revenue of the GGC algorithm based on multi-linear programming for solving the A and B game patrol models was (15.0, -30.0) and (21.1, -38.2), respectively, which were superior to other strategies. The above data indicates that the research method can improve patrol efficiency and comprehensive coverage, providing strong support for optimizing social security patrol strategies.https://doi.org/10.1007/s42452-025-07386-3Graph theoryNetwork graph modelSocial securityPatrol strategyIntelligent patrol agentGeneralized geometric coverage algorithm |
| spellingShingle | Jian Wang Optimization of social security patrol strategy based on graph theory and GGC algorithm Discover Applied Sciences Graph theory Network graph model Social security Patrol strategy Intelligent patrol agent Generalized geometric coverage algorithm |
| title | Optimization of social security patrol strategy based on graph theory and GGC algorithm |
| title_full | Optimization of social security patrol strategy based on graph theory and GGC algorithm |
| title_fullStr | Optimization of social security patrol strategy based on graph theory and GGC algorithm |
| title_full_unstemmed | Optimization of social security patrol strategy based on graph theory and GGC algorithm |
| title_short | Optimization of social security patrol strategy based on graph theory and GGC algorithm |
| title_sort | optimization of social security patrol strategy based on graph theory and ggc algorithm |
| topic | Graph theory Network graph model Social security Patrol strategy Intelligent patrol agent Generalized geometric coverage algorithm |
| url | https://doi.org/10.1007/s42452-025-07386-3 |
| work_keys_str_mv | AT jianwang optimizationofsocialsecuritypatrolstrategybasedongraphtheoryandggcalgorithm |