Optimizing Police Patrol Strategies in Real-World Scenarios: A Modified PPS-MOEA/D Approach for Constrained Multi-Objective Optimization
This study addresses the realistic constrained multi-objective optimization problem of police patrols by constructing a mathematical model tailored to the actual operational context of police patrols in China. To solve this problem, a modified PPS-MOEA/D algorithm is proposed and its performance is...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/7/3651 |
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| author | Jinguang Sui Peng Chen Huan Jiang |
| author_facet | Jinguang Sui Peng Chen Huan Jiang |
| author_sort | Jinguang Sui |
| collection | DOAJ |
| description | This study addresses the realistic constrained multi-objective optimization problem of police patrols by constructing a mathematical model tailored to the actual operational context of police patrols in China. To solve this problem, a modified PPS-MOEA/D algorithm is proposed and its performance is systematically evaluated against several state-of-the-art Constrained Multi-Objective Evolutionary Algorithms (CMOEAs). The results demonstrate the superiority of the proposed approach in terms of the solution quality and computational efficiency. Furthermore, the optimal solution set is discussed and visualized on a map, providing decision makers with practical and actionable insights that align with real-world patrol requirements. This research not only advances the theoretical framework for police patrol optimization, but also offers a practical tool for enhancing the effectiveness and efficiency of law enforcement operations in urban environments. |
| format | Article |
| id | doaj-art-8d3516bb80fa45d2bc4530c1f61ed099 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-8d3516bb80fa45d2bc4530c1f61ed0992025-08-20T02:09:18ZengMDPI AGApplied Sciences2076-34172025-03-01157365110.3390/app15073651Optimizing Police Patrol Strategies in Real-World Scenarios: A Modified PPS-MOEA/D Approach for Constrained Multi-Objective OptimizationJinguang Sui0Peng Chen1Huan Jiang2School of Information Network Security, People’s Public Security University of China, Beijing 100038, ChinaSchool of Information Network Security, People’s Public Security University of China, Beijing 100038, ChinaSchool of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, ChinaThis study addresses the realistic constrained multi-objective optimization problem of police patrols by constructing a mathematical model tailored to the actual operational context of police patrols in China. To solve this problem, a modified PPS-MOEA/D algorithm is proposed and its performance is systematically evaluated against several state-of-the-art Constrained Multi-Objective Evolutionary Algorithms (CMOEAs). The results demonstrate the superiority of the proposed approach in terms of the solution quality and computational efficiency. Furthermore, the optimal solution set is discussed and visualized on a map, providing decision makers with practical and actionable insights that align with real-world patrol requirements. This research not only advances the theoretical framework for police patrol optimization, but also offers a practical tool for enhancing the effectiveness and efficiency of law enforcement operations in urban environments.https://www.mdpi.com/2076-3417/15/7/3651police patrol optimizationconstrained multi-objective optimizationPPS-MOEA/DCMOEAs |
| spellingShingle | Jinguang Sui Peng Chen Huan Jiang Optimizing Police Patrol Strategies in Real-World Scenarios: A Modified PPS-MOEA/D Approach for Constrained Multi-Objective Optimization Applied Sciences police patrol optimization constrained multi-objective optimization PPS-MOEA/D CMOEAs |
| title | Optimizing Police Patrol Strategies in Real-World Scenarios: A Modified PPS-MOEA/D Approach for Constrained Multi-Objective Optimization |
| title_full | Optimizing Police Patrol Strategies in Real-World Scenarios: A Modified PPS-MOEA/D Approach for Constrained Multi-Objective Optimization |
| title_fullStr | Optimizing Police Patrol Strategies in Real-World Scenarios: A Modified PPS-MOEA/D Approach for Constrained Multi-Objective Optimization |
| title_full_unstemmed | Optimizing Police Patrol Strategies in Real-World Scenarios: A Modified PPS-MOEA/D Approach for Constrained Multi-Objective Optimization |
| title_short | Optimizing Police Patrol Strategies in Real-World Scenarios: A Modified PPS-MOEA/D Approach for Constrained Multi-Objective Optimization |
| title_sort | optimizing police patrol strategies in real world scenarios a modified pps moea d approach for constrained multi objective optimization |
| topic | police patrol optimization constrained multi-objective optimization PPS-MOEA/D CMOEAs |
| url | https://www.mdpi.com/2076-3417/15/7/3651 |
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