易腐商品定价模型及其粒子群解法

论文研究了易腐商品的定价问题,并基于随机需求分布假设和利润最大化原则提出了一种新的易腐商品最优定价模型。多个随机分布的存在使该模型比传统模型更加复杂,因此难以使用常规函数极值法获得解析解,论文尝试将粒子群优化算法引入该模型进行演化求解。最后给出的算例分析表明:该模型和算法可以快速有效地解决随机需求情况下的易腐商品最优定价问题。

Optimal Pricing Model for Perishable Commodities and its Particle Swarm Optimization Solution

The pricing problem for perishable commodities is considered in this paper.And a new model is presented based on the profit maximization principle and a discrete demand function which involves the demand rate,buyers' preferences,and a negative binomial distribution.Because of the existence of some different stochastic distributions,this new model is more sophisticate than those in extant literature,which causes the difficulty in solving it with the normal numerical methods.In this context,this paper tries introducing the particle swarm optimization(PSO) algorithm to solve this new model.Then a PSO program scheme is designed and a case study is presented,which indicates that this model and algorithm are able to derive optimal prices quickly and effectively.At last,some possible extensions to this model are presented.