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Title Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China
ID_Doc 37261
Authors Jiang, YR; Li, HW; Feng, BB; Wu, ZK; Zhao, S; Wang, ZH
Title Street Patrol Routing Optimization in Smart City Management Based on Genetic Algorithm: A Case in Zhengzhou, China
Year 2022
Published Isprs International Journal Of Geo-Information, 11.0, 3
DOI 10.3390/ijgi11030171
Abstract A series of urban law enforcement events involving city inspectors dispatched by the city management department can reflect some problems in smart city management, such as illegal advertising and unlicensed street operation. In this paper, we propose a model for the allocation of city inspectors and the optimization of patrol paths. The objective is to minimize the average response time and the number of inspectors. We also develop a priority-patrol-and-multiobjective genetic algorithm (DP-MOGA) to classify patrol segments according to the frequency of events and develop an improved genetic algorithm to achieve the aforementioned objective. We conduct numerical experiments using patrol data obtained from city inspectors in Zhengzhou, China, to clearly show that the proposed algorithm generates reasonable routes that reduce the average response time of events and the number of patrol inspectors. Furthermore, we test the algorithm for three different time scenarios (roads with different average numbers of events) and demonstrate the efficiency of the algorithm. The experimental results show that our proposed algorithm is more stable and efficient than other existing algorithms.
Author Keywords patrol routing optimization; smart city management; road segment classification; genetic algorithm
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
EID WOS:000775279900001
WoS Category Computer Science, Information Systems; Geography, Physical; Remote Sensing
Research Area Computer Science; Physical Geography; Remote Sensing
PDF https://www.mdpi.com/2220-9964/11/3/171/pdf?version=1646641367
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