摘要
综合考虑战时物流配送车辆路径问题(VRP)的多目标评价,提出多属性道路网络下战时物流配送的VRP算法,并建立完全分层优化模型。将进化算法与传统优化技术相结合,构造了模型的两层求解算法,第一层采用遗传算法和模拟退火算法混合的GASA算法,第二层采用枚举法。并以成品燃油配送为例进行了实验,结果表明算法较标准遗传算法更有效。
Through considering the multi-objective evaluation of vehicle routing problem （VRP） of logistics distribution in wartime, the essay describes VRP algorithm of wartime distribution in multi-attribute road networks, and establishes completely hierarchical optimization model. Two solution algorithms are established through combining the evolving algorithm with traditional optimization technology, firstly, adopting the Genetic Simulated Annealing Algorithms （GASA）; secondly, adopting the enumeration algorithm. The experiment is implemented with the example of finished fuel distribution, the results indicate that the GASA has higher efficiency than standard genetic algorithms.
出处
《铁道运输与经济》
北大核心
2007年第7期71-74,共4页
Railway Transport and Economy
关键词
物流配送
路径优化
目标函数
模型
Logistics Distribution
Routing Optimization
Object Function
Model
