模糊环境下边境反恐交通网络设计模型及应用  

Optimal Model and Application for Terrorist Interdiction Network Design under Fuzzy Environment

作　　者：项寅 XIANG Yin(School of Business,University of Science and Technology of Suzhou,Suzhou 215009,China)

机构地区：[1]苏州科技大学商学院,江苏苏州215009

出　　处：《中国管理科学》2021年第11期237-248,共12页Chinese Journal of Management Science

基　　金：国家自然科学基金资助项目(72104170);教育部人文社会科学基金资助项目(21YJC630141)。

摘　　要："一带一路"倡议加深了我国与邻国的交流,也为境外恐怖分子潜入提供可乘之机。政府可通过在交通网络中有效地分配阻断(或安检)资源,来提前识别和拦截正在潜入的恐怖分子。特别地,考虑各路段阻断资源需求、袭击后果为模糊不确定的情形,结合政府与恐怖分子的互动行为构建双层规划模型,并设计一类改进遗传算法求解。最后,结合南疆交通网络进行仿真分析,结果发现:通过边境反恐交通网络设计可以降低境内恐袭风险,恐怖分子偏好袭击边境口岸城市和境内重要城市,政府应优先针对口岸城市周围路段实施强化安检,还须重视安检资源投入的"边际效用递减规律",以及安检资源和安检能力间的"替代关系",合理优化两者比例,提高反恐效率。Since the September 11 attacks, terror has become a major threat in the world. Recently, with the implementation of the Belt and Road initiative, the cooperation between China and other countries are becoming more and more frequently, which increases the risk for terrorist invasion. In order to prevent terrorists abroad from invading into China, the government can design an effective interdiction network in the border area.A counter-terrorism interdiction network design problem is considered which is in essence a security resources allocation problem in a fixed transportation network. This problem is modeled as a leader-follower game. The leader(e.g. the government, public security departments) moves first to interdict a portion of edges of the network, the function of interdiction is to decrease a terrorist’s passing probability on the interdicted edges. After observing the leader’s action, the follower(e.g. the terrorist) makes a best response to first select the attack node and then optimize the invasion route between a fixed source node and the attack node. In this context, how the leader optimizes the allocation of security resources in the network to reduce the risk of attack is studied. Different from previous studies, the fuzziness of the network is considered and the attack node is taken as a decision variable of the follower.Above leader-follower game is addressed as a bi-level programming model. The upper-level programming refers to the resource allocation problem of the leader, and the lower-level programming is associated to the follower’s target selecting and intrusion path optimization. In order to solve this model, a hybrid algorithm is proposed, where an improved genetic algorithm is used in the upper level program for enumerating and updating interdict plans, and the an exact algorithm is designed for solving the lower level problem when the interdict plans are fixed.Our model and algorithm are tested in the transportation network of Southern Xinjiang. The numerical results show that:(i) t

关 键 词：模糊不确定 反恐 网络设计 双层规划 遗传算法 

分 类 号：O225[理学—运筹学与控制论] F224.32[理学—数学]