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个人信息Personal Information
教授
博士生导师
硕士生导师
主要任职：Director of Academic Committee at Kaifa District
其他任职：开发区校区学术分委员会主任（Director of Academic Committee at Kaifa Campus）
性别：男
毕业院校：多伦多大学
学位：博士
所在单位：软件学院、国际信息与软件学院
学科：软件工程. 运筹学与控制论
办公地点：开发区（Kaifa District Campus）
联系方式：mingchul@dlut.edu.cn
电子邮箱：mingchul@dlut.edu.cn
Optimal Allocation Strategy Based on Stackelberg Game for Inspecting Drunk Driving on Traffic Network
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论文类型：期刊论文
发表时间：2017-12-31
发表刊物：KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
收录刊物：SCIE、EI
卷号：11
期号：12
页面范围：5759-5779
ISSN号：1976-7277
关键字：Stackelberg game; resource allocation; security; optimization; drunk driving
摘要：As the main means to cope with the stubborn problem of drunk driving, the inspection of drunk driving has already been paid more attention and thus reinforced. In this paper, we model this scenario as a Stackelberg game, where the police department (called defender) allocates resources dynamically in terms of the traffic situation on the traffic network to arrest drink drivers and drivers who drink (called attacker), whether choosing drunk driving or designated driving service, expect to minimize their cost for given travel routes. However, with the number of resources are limited, our goal is to calculate the optimal resource allocation strategy for the defender. Therefore, first, we provide an effective approach (named OISDD) to fulfill our goal, i.e., generate the optimal strategy to inspect drunk driving. Second, we apply OISDD to directed graphs (which are abstracted from Dalian traffic network) to analyze and test its correctness and rationality. The experimental results show that OISDD is feasible and efficient.