Research of order allocation model based on cloud and hybrid genetic algorithm under ecommerce environment

For massive order allocation problem of the third party logistics (TPL) in ecommerce, this paper proposes a general order allocation model based on cloud architecture and hybrid genetic algorithm (GA), implementing cloud deployable MapReduce (MR) code to parallelize allocation process, using heuristic rule to fix illegal chromosome during encoding process and adopting mixed integer programming (MIP) as fitness function to guarantee rationality of chromosome fitness. The simulation experiment shows that in mass processing of orders, the model performance in a multi-server cluster environment is remarkable superior to that in stand-alone environment. This model can be directly applied to cloud based logistics information platform (LIP) in near future, implementing fast auto-allocation for massive concurrent orders, with great application value.     

自动事件检测算法的比较及评估

对现有的几种典型的高速公路事件自动检测算法的性能进行了评价,并给出各种算法的优缺点及比较评估标准,采用检测率(DR)和误报率(FAR)特征曲线及模拟退火算法进行了评价和优化,在比较、分析结果的基础上提出了智能检测算法的概念,并指出其今后的发展趋势。