餐厅预定O-L预测模型与营运策略的改进  

Restaurant Predetermined O-L Prediction Model and Improved Operating Strategy

作　　者：田镇滔 何晓燕[1] 姚学香 杨晓菊[1] 沈田鋆 

机构地区：[1]四川师范大学数学与软件科学学院,成都610066

出　　处：《成都工业学院学报》2016年第2期53-55,共3页Journal of Chengdu Technological University

基　　金：四川师范大学2015年国家级"大学生创新创业训练计划"项目"预定O-L预测模型与运营策略改进"(201510636041)

摘　　要：针对餐厅预定超额与不足问题,基于BP神经网络模型和灰色预测模型GM(1,n),建立餐厅超额预定与预定不足(OL)预测模型。借助GM(1,n)模型对影响因素进行评估,通过考虑价格、就餐满意强度、时间段、等待时间、厨师效率和餐厅容量等6个因素,分析各因素的作用程度和机会成本,对边际收益最高的因素进行改进。让商家在改进经营策略时找到侧重方向,帮助餐厅及时调整经营方式和策略,在不损失顾客的前提下获得最大利润。Aiming at restaurant predetermined problem in excess and shortage,the authors established a predetermined over booking and inadequate model based on the BP neural net work model and gray GM （1,n）model. Many alternative factors were taken into account according to the model GM （1,n）,in which six factors such as the level of consumption,dining satisfaction,period of eating,waiting time,cook efficiency and restaurant capacity,were considered. By the Analysis of the role of various factors and opportunity cost,the highest marginal income factor could be improved, which helped the businesses find focused direction in the improvement of business strategy. Then,it could assist restaurants in making a timely adjustment of management style and obtaining the maximum profit under the premise without losing a customer.

关 键 词：预定O-L预测模型 BP神经网络 灰色预测 策略改进 客流量分析 

分 类 号：O159[理学—数学]