Network Optimization for Improving Security and Safety Level of Dangerous Goods Transportation Based on Cloud Computing

Abstract

Network optimisation for improving security and safety level of dangerous goods transportation (NOISSLDGT) belongs to NP-hard problems with strict constraints, and that makes it harder to solve. In order to dealing with NOISSLDGT, an improved risk analysis which combining the features and factors was devised. A network optimisation model to minimise the total cost was established considering the network capacity and the maximum risk limits. The problem has been discussed with LINGO first. Furthermore, the cloud computing technology is introduced, and the task scheduling in cloud computing environment was analysed. Based on cloud computing task scheduling, a detailed design of the simulated annealing algorithm (SAA) was presented. An example was analysed to demonstrate that the improved algorithms are efficient and feasible in solving NOISSLDGT.