摘要
从航空公司的角度,针对需求函数参数的不确定性,以风险最小收益最大化为目标,结合货物体积、质量的二维约束,运用相对熵理论,建立多周期航空货运动态定价鲁棒优化模型,设计了该模型的改进人工蜂群算法。结合模拟数据分析,验证了该模型和算法的有效性。
Aimed at minimizing the risk of pricing under demand uncertainty and maximizing the income of air cargo for an airline,a robust dynamic pricing model of air cargo was established based on relative entropy while considering the weight and volume constraints of goods.An improved artificial bee colony algorithm was used to solve the model.Numerical results show that this approach provides optimized pricing decisions which can generate more profit while lower risks.
出处
《武汉理工大学学报（信息与管理工程版）》
CAS
2013年第3期418-422,共5页
Journal of Wuhan University of Technology：Information & Management Engineering
关键词
航空货运
收益管理
动态定价
鲁棒优化
人工蜂群算法
air cargo
revenue management
dynamic pricing
robust optimization
artificial bee colony algorithm
