Dynamic pricing model and algorithm for perishable products with fuzzy demand
Dynamic pricing model and algorithm for perishable products with fuzzy demand
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DOI：
10.1002/asmb.816
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发表时间：
2010-11
影响因子：
1.4
通讯作者：
Y. Xiong;Gendao Li;K. Fernandes
中科院分区：
文献类型：
--
作者：
Y. Xiong;Gendao Li;K. Fernandes
本文研究了在有限期限内销售易腐物品固定库存的动态定价问题，其中决策者没有必要的历史数据来估计不确定需求的分布，但对数量需求的信息不准确。我们使用模糊变量对这种不确定性进行建模。基于可信度理论的动态定价问题采用三种模糊规划模型来表述，即：模糊期望收益最大化模型、α-乐观收益最大化模型和可信度最大化模型。给出了具有模糊参数的函数的模糊模拟并将其嵌入到遗传算法中，以设计混合智能算法来求解这三个模型。最后，提出了一个现实世界的例子来强调所开发的模型和算法的有效性。版权所有 © 2009 约翰·威利父子有限公司
This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, α-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm. Copyright © 2009 John Wiley & Sons, Ltd.