摘要
为了实现物流资源利用率的提高和物流成本的降低,根据"云"的思想,建立了云物流下基于最大覆盖的选址—分配的多目标非线性决策模型,该模型的目标是配送中心的选址优化和整体需求覆盖最大化。设计了基于遗传和粒子群的组合式启发式算法,对算法的性能进行了Benchmark测试。通过大量算例和对比分析,验证了模型和算法的有效性和稳定性。
In order to improve the logistics resource utilization rate and reduce the logistics cost,under the guidance of the ＂cloud＂ thought,this paper constructed a new multi-objective and non-linear location-distribution model with certain assumptions as premises.The model aimed to the maximal covering demand,the optimal distribution and the lowest cost of the supply chain.It designed the heuristic algorithm based on GA and PSO for the model according to the specific structure of the model＇s decision-making space.The numerical calculation was performed to solve the arithmetic problem in practical investigation.It shows that the decision model is practical and the algorithm is valid.
出处
《计算机应用研究》
CSCD
北大核心
2012年第10期3640-3644,共5页
Application Research of Computers
基金
湖北省自然科学基金重点资助项目(2010CDA022)
湖北省软科学研究专项(RKF0069)
湖北省社科"十二五"规划资助项目
关键词
云物流
最大覆盖
选址—分配模型
多目标决策
启发式算法
cloud logistics
maximal covering
location-distribution model
multi-objective decision
heuristic algorithm
