摘要
考虑消费者购买行为,建立生鲜食品多阶段动态定价模型,力图使零售价格能够动态地反映生鲜食品的价值波动,采用基于正负反馈机制的改进蚁群算法求解模型。通过不同算例仿真分析,表明该模型优于传统模型;同时将本文算法与其他3种算法进行对比,从收敛性能和运行时间方面证实本文算法更优。
Considering buyers behaviors,multi-period dynamic pricing model for fresh foods is deduced,which tries to make retail price reflect the value of the product warily.And an improved ant colony algorithm based on plus/minus feedback mechanism is proposed to resolve this model.Analysis of different numerical examples indicates that this model is superior to traditional models.Comparing with other three different algorithms,the validity of proposed algorithm can be approved from two aspects： convergence capability and computation time.
出处
《系统管理学报》
CSSCI
北大核心
2010年第2期140-146,151,共8页
Journal of Systems & Management
基金
"十一五"国家科技支撑计划重大资助项目(2006BAK02A16
2006BAK02A28)
国家自然科学基金项目(60872075)
江苏省六大人才高峰项目
关键词
随机需求
动态定价
生鲜食品
蚁群算法
stochastic demand
dynamic pricing
fresh foods
ant colony algorithm
