基于粒子群算法和时空网络的航班舱位控制研究  

Researching Flight Seat Inventory Control Based on PSO Algorithm and Spatio-temporal Network

作　　者：乐美龙[1] 高金敏 

机构地区：[1]上海海事大学科学研究院,上海201306

出　　处：《科技通报》2014年第11期185-189,共5页Bulletin of Science and Technology

基　　金：上海市自然科学基金创新行动计划项目(编号:10190502500)

摘　　要：航班舱位控制是航空公司收益管理的核心,截止到目前为止,收益管理中有关舱位优化控制问题一般都是基于单航段、多航段、轮辐式等航线网络来进行建模分析和研究。本文从实际航班运行的角度出发,构造航班运行时空网络,建立基于时空网络的舱位控制优化模型,并运用粒子群算法对模型进行求解。研究结果证明了模型的有效性。此外,将粒子群算法应用于此舱位优化控制模型,可得到满意的解,该算法简化了变量间复杂的约束关系,易于实现,具有明显的优势。Seat inventory control is the core of airline revenue management, as so far, optimal control problems in airline revenue management are usually based on a single flight, flight segments, hub-and-spokes route network model for research. This paper constructs flights running spatio-temporal network, establish seat inventory optimization models based on spatio-temporal network and use Particle Swarm Optimization algorithm for solving. Research results show the validity of these models. In addition, satisfactory solution can be obtained through using particle swarm optimization algorithm. This algorithm simplifies the complexity of constraint and can be easily accomplished. It has an obvious advantage.

关 键 词：舱位控制 轮辐式航线 时空网络 粒子群算法 

分 类 号：V2[航空宇航科学技术]