摘要
模糊需求可回程取货车辆路径问题是运筹学领域研究的一个热点问题.文中构建该问题的数学模型,并提出一种改进的人工鱼群算法.将人工鱼群算法仿生学原理和决策者主观偏好进行有效结合,重构人工鱼群算法的寻优公式,通过动态调整人工鱼移动步长、视野范围和邻域值等方法提高寻优能力.仿真实验结果证实该算法的有效性和优越性.
The vehicle routing problem with backhaul and fuzzy demand （VRPBFD） is one of the most important and difficult problems in operational research filed. A mathematical model for the problem is built in this paper and the improved artificial fish swarm algorithm is proposed. With the effective combination of bionic principle in artificial fish swarm algorithm and subjective preference from decision maker, the optimization function is reconstructed. The optimization ability is raised by dynamically adjusting moving steps of artificial fishes, visual range and neighborhood values. The experiment results of simulation show that the improved algorithm has the validity and superiority.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
2010年第4期560-564,共5页
Pattern Recognition and Artificial Intelligence
基金
浙江省教育厅科技资助项目(No.06JK258)
关键词
可回程取货车辆路径问题(VRPB)
模糊需求
群智能优化
人工鱼群算法
Vehicle Routing Problem with Backhaul （VRPB）, Fuzzy Demand, Swarm IntelligenceOptimization, Artificial Fish Swarm Algorithm
