Chance Constrained Optimization for Targeted Internet Advertising

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

Applications of Chance Constrained Optimization in Operations Management

In this thesis we explore three applications of chance constrained optimization in operations management. We first investigate the effect of consumer demand estimation error on new product production planning. An inventory model is proposed, whereby demand is influenced by price and advertising. The effect of parameter misspecification of the demand model is empirically examined in relation to profit and service level feasibility, and conservative approaches to estimating their effect on consumer demand is determined. We next consider optimization in Internet advertising by introducing a chance constrained model for the fulfillment of guaranteed display Internet advertising campaigns. Lower and upper bounds using Monte Carlo sampling and convex approximations are presented, as well as a branching heuristic for sample approximation lower bounds and an iterative algorithm for improved convex approximation upper bounds. The final application is in risk management for parimutuel horse racing wagering. We develop a methodology to limit potential losing streaks with high probability to the given time horizon of a gambler. A proof of concept was conducted using one season of historical race data, where losing streaks were effectively contained within different time periods for superfecta betting

Personalized advertisement assignment system

This thesis presents a comprehensive framework which will be used to maximize the advertising revenues of a company that develops a 3-D virtual reality social platform. The comprehensive framework includes the development of a personalized advertising business model for the company, representation of the business model with a mathematical program and proposing a set of heuristic solutions for the personalized advertising problem. The proposed heuristics are developed and their performances are compared with an experimental analysis under various conditions