摘要
在物流资金既定的情况下,不同的定价方案,物流企业的获利不同,为了获得更优的物流服务定价决策方案,提高收益率,提出一种改进人工鱼群算法的物流服务定价决策模型。首先建立物流服务定价决策数学模型,模型对物流企业各环节设置参数,定量地衡量这些指标对资金的消耗,然后采用人工鱼群算法对模型进行求解,在求解过程中,利用混沌运动的遍历性,对物流车辆的增加、仓库动态容量的优化、物流人员培训的最佳人数进行了混沌遍历分析,解决了人工鱼群算法对这些物流参数分析时易陷入局部最优的难题,并结合反馈策略,提高了人工鱼群算法对物流参数的求解效率,节约了成本,实现了利益最大化。仿真结果表明,改进人工鱼群算法可以获得使物流企业更加满意的服务定价决策方案,提高了收益率,降低了风险。
In this paper, we proposed the pricing decision model for the logistics services on the basis of the improved artificial fish swarm algorithm. First we built the mathematic model of the pricing decisions for logistics services, then solved it using the artificial fish swarm algorithm after improving it by correcting its tendency toward local optimization, and next in connection with the feedback strategy, improved the efficiency of the artificial fish swarm algorithm in solving the logistics parameters to reduce cost and realize maximum revenue. At the end, through a simulation, we found that the artificial fish swarm algorithm could satisfactorily provide service pricing solutions for the logistics enterprises.
出处
《物流技术》
北大核心
2014年第3期300-302,305,共4页
Logistics Technology
基金
河南省交通厅立项项目"中原经济区物流人才需求及岗位能力分析"(2012P63)
河南省重点科技攻关项目(122102210086)
河南省教育厅自然基金资助项目(2011A520026)
关键词
物流企业
服务定价决策
收益率
人工鱼群算法
混沌运动
反馈策略
logistics enterprise
service pricing decision
yield return
artificial fish swarm algorithm
chaotic motion
feedback strategy
