多阶段多目标洗钱网络路径算法研究及反洗钱应对策略

Research on multi-stage and multi-object money laundering network path algorithm and the anti-money laundering strategies

针对多阶段非法资金转移的路径优化问题,基于多目标优化的思想,构建了以洗钱量最大化、风险最小化及时间最短化为决策目标的多阶段洗钱网络路径优化模型;并利用期望效用理论对不法公职人员的风险偏好进行研究,分析出不同时间压力下不同风险偏好的不法公职人员对洗钱目标的五种不同选择,运用多重动态规划法以及最大流理论针对每种洗钱目标选择基于模型提出相应的算法,并通过实例应用验证算法的可行性.最后,从裸官外逃、大额交易、洗钱犯罪的心理过程、交易时间等方面提出了防范不法公职人员洗钱犯罪的措施及建议.

In view of the path optimization problem of multi-stage illegal money transfers, based on the idea of muti-objective optimization, this paper constructed a multi-stage network path optimization model of money laundering with money laundering maximization, risk minimization and the amount of time to be shortest as decision-making targets. The expected utility theory was used to research the risk preference of illegal civil servants, and to analyze the five different choices of illegal civil servants under the different time pressure. In addition, each target selection based on this model was put forward by using the theory of multiple dynamic programming and maximum flow, and its feasibility of the algorithm was validated by application instance. Finally, some measure and suggestions to prevent illegal civil servants from money laundering crime were proposed from the naked official flight, big deals, money laundering crime psychological process to transaction time.