摘要
研究逢低买入拍卖中最优定价问题。由于逢低买入拍卖中卖方期望收益函数异常复杂,常规函数极值法具有极大局限性,无法获得最优价格策略,提出一种带极值扰动算子的QPSO(Quantum-behaved Particle Swarm Optimization)算法对模型进行优化和数值计算。算例表明该算法可以快速有效地找到最优价格策略,且具有较好的全局收敛能力。
The optimal pricing problem with the group-buying auction is mainly studied.Since the function of seller’s expected revenue is difficult for the normal function optimization methods to solve,the QPSO with the extremum disturbed arithmetic operators is introduced to settle it.Then the program scheme is designed and the numerical example is provided,which indicates that the algorithm is able to derive optimal prices quickly and effectively,and the global convergence property of the algorithm is proved.
出处
《计算机工程与应用》
CSCD
北大核心
2008年第8期210-211,216,共3页
Computer Engineering and Applications
基金
四川省教育厅青年基金项目(No.2005B025)
