摘要
座位优化控制是航空运输界增加利润的有效方法 .基于旅客的需求预测 ,可以利用数学规划模型为不同的航段和票价组合计算座位销售上限或者销售竞价 ,从而达到单个航班收入最大化的目的 .常用的方法可分为确定模型和概率模型 ,但对多航段多舱位的优化问题 ,由于出现了复杂的组合和约束 ,这些模型必须简化 .提出了基于遗传算法的座位优化控制模型 ,并和常用的优化方法进行了仿真对比 .研究结果表明 ,遗传算法应用于座位优化 ,可得到满意的解 ,同时 ,遗传算法简化了复杂的约束关系 ,易于实现 ,具有明显的优势 .
Airline seat inventory control is a very profitable tool in the airline industry. Mathematical programming models provide booking limits or bid-prices for all itineraries and fare classes based on demand forecasts. The general models include deterministic approximation methods and probabilistic approximation methods, but these models are hard to solve if the number of decision variables and constraints is large. We present a new model for seat inventory control based on genetic algorithm in this paper, and simulate results was compared among the new model and general models. Study shows that Genetic algorithm is profit for seat inventory control, and it is easy to implement.
出处
《数学的实践与认识》
CSCD
北大核心
2004年第4期38-43,共6页
Mathematics in Practice and Theory
基金
国家自然科学基金 ( 60 1 740 2 1 )
中国民航总局教育研究项目 ( 2 0 0 3 -0 3 -0 5 )资助
