Network optimisation for improving security and safety level of dangerous goods transportation based on cloud computing

Haixing Wang, Guiping Xiao, Zhen Wei, Tao Hai
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引用次数: 3

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.
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基于云计算的提升危险品运输安全保障水平的网络优化
提高危险品运输安全和安全水平的网络优化(NOISSLDGT)属于NP-hard问题,具有严格的约束条件,求解难度较大。为了处理噪声sldgt,设计了一种特征与因素相结合的改进风险分析方法。考虑网络容量和最大风险限制,建立了以总成本最小为目标的网络优化模型。这个问题已经先和LINGO讨论过了。进一步介绍了云计算技术,分析了云计算环境下的任务调度问题。基于云计算任务调度,给出了模拟退火算法(SAA)的详细设计。算例分析表明,改进算法在求解噪声sldgt中是有效可行的。
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