A non-parametric approach to demand forecasting in revenue management

被引：11

作者：

Azadeh, Sh. Sharif ^{[1
]}

Marcotte, P. ^{[2
]}

Savard, G. ^{[1
]}

机构：

[1] Polytech Montreal, Dept Math & Ind Engn, Montreal, PQ H3C 3A7, Canada

[2] Univ Montreal, Dept Comp Sci & Operat Res, Montreal, PQ H3T 1J4, Canada

来源：

COMPUTERS & OPERATIONS RESEARCH | 2015年 / 63卷

关键词：

Revenue management; Forecasting; Integer programming; Branch-and-bound; Heuristics; FUTURE; MODEL;

D O I：

10.1016/j.cor.2015.03.015

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In revenue management, the profitability of the inventory and pricing decisions rests on the accuracy of demand forecasts. However, whenever a product is no longer available, true demand may differ from registered bookings, thus inducing a negative bias in the estimation figures, as well as an artificial increase in demand for substitute products. In order to address these issues, we propose an original Mixed Integer Nonlinear Program (MINLP) to estimate product utilities as well as capturing seasonal effects. This behavioral model solely rests on daily registered bookings and product availabilities. Its outputs are the product utilities and daily potential demands, together with the expected demand of each product within any given time interval. Those are obtained via a tailored algorithm that outperforms two well-known generic software for global optimization. (C) 2015 Elsevier Ltd. All rights reserved.

引用

页码：23 / 31

页数：9

共 27 条

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