基于云计算神经网络物流车辆调度算法研究

研究了物流车辆调度优化问题。针对云计算下任务调度算法没有考虑调度的服务质量和用户满意度的问题,特别是在物流任务调度问题中存在复杂的计算网络,造成计算率降低,为了解决上述问题,提出了一种新的有关云计算和神经网络相结合的物流作业调度算法。算法充分考虑了调度的服务质量以及用户满意度,建立一个参数化的处理模型,计算用户在各个资源上的综合满意度,再将任务分配到满足用户需求和使系统资源达到均衡的资源上执行,最后采用改进的神经网络进行优化车辆调度。实验结果表明,改进算法不仅能满足用户的多种需求,提高了用户的满意度,同时也提高了资源调度率和系统资源的利用率。

Study on the Logistics Vehicle Scheduling Based on Cloud Computing and Neural Network

the study of logistics vehicle scheduling optimization problems.For cloud computing task scheduling algorithm does not consider the scheduling of service quality and customer satisfaction problem,put forward a kind of new based on cloud computing and neural network combining logistics scheduling algorithm.The algorithm takes full account of the scheduling of service quality and customer satisfaction,establish a parametric model,calculate the user in various resources on the comprehensive satisfaction,to assign tasks to meet the needs of users and make the system resources to achieve the equilibrium resource for execution,finally using the improved neural network for optimization of vehicle dispatching.The experimental results show that the algorithm can not only meet the various needs of customers,improve customer satisfaction,but also improve the rate of resource scheduling and the utilization of system resources.