Revenue Optimization with Price-Sensitive and Interdependent Demand
Julien Laasri, Marc Revol

TL;DR
This paper focuses on optimizing airline ticket prices and quantities to maximize revenue for a direct flight, assuming demand data and price options are predetermined and given by airline algorithms.
Contribution
It introduces a revenue optimization model specifically for airline ticket sales considering price-sensitive and interdependent demand, with demand data and prices assumed to be known.
Findings
Maximized revenue through optimal pricing strategies.
Validated model effectiveness with real airline data.
Demonstrated impact of demand interdependence on pricing decisions.
Abstract
As Kalyan T. Talluri and Garrett J. Van Ryzin describe in their work [3], Revenue Management aims to maximize an organization's revenue by considering three types of decision categories: structural, pricing, and quantity. In this document, our primary focus will be on decisions related to pricing and quantity for the sale of airline tickets on a direct flight over a certain number of time periods. More specifically, we will only focus on the optimization aspect of this problem. We will assume the demand data to be given, since Air France estimates it beforehand using real data. Similarly, we assume all price options to be predetermined by Air France's algorithms and verified by their analysts. Our objective will be to maximize the revenue of a direct flight by choosing the prices for each product from the predefined set of options. -- Comme d\'ecrit par Kalyan T. Talluri et Garrett…
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Taxonomy
TopicsSupply Chain and Inventory Management · Auction Theory and Applications · Aviation Industry Analysis and Trends
MethodsFocus · Sparse Evolutionary Training
