Chance constrained optimization for targeted Internet advertising

被引:18
|
作者
Deza, Antoine [1 ]
Huang, Kai [2 ]
Metel, Michael R. [3 ]
机构
[1] McMaster Univ, Dept Comp & Software, Adv Optimizat Lab, Hamilton, ON, Canada
[2] McMaster Univ, DeGroote Sch Business, Hamilton, ON, Canada
[3] McMaster Univ, Sch Computat Sci & Engn, Hamilton, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Internet advertising; Chance constrained programming; Sample approximation; Convex programming;
D O I
10.1016/j.omega.2014.12.007
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
We introduce a chance constrained optimization model for the fulfillment of guaranteed display Internet advertising campaigns. The proposed formulation for the allocation of display inventory takes into account the uncertainty of the supply of Internet viewers. We discuss and present theoretical and computational features of the model via Monte Carlo sampling and convex approximations. Theoretical upper and lower bounds are presented along with a numerical substantiation. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:90 / 96
页数:7
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