scholarly journals Uncertain Programming for Network Revenue Management

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Deyi Mou ◽  
Xiaoxin Wang

The mathematical model for airline network seat inventory control problem is usually investigated to maximize the total revenue under some constraints such as capacities and demands. This paper presents a chance-constrained programming model based on the uncertainty theory for network revenue management, in which the fares and the demands are both uncertain variables rather than random variables. The uncertain programming model can be transformed into a deterministic form by taking expected value on objective function and confidence level on the constraint functions. Based on the strategy of nested booking limits, a solution method of booking control is developed to solve the problem. Finally, this paper gives a numerical example to show that the method is practical and efficient.

2020 ◽  
Vol 68 (3) ◽  
pp. 834-855 ◽  
Author(s):  
Yuhang Ma ◽  
Paat Rusmevichientong ◽  
Mika Sumida ◽  
Huseyin Topaloglu

Many revenue management problems require making capacity control and pricing decisions for multiple products. The decisions for the different products interact because either the products use a common pool of resources or the customers choose and substitute among the products. When pricing airline tickets, for example, different itinerary products use the capacities on common flight legs and the customers choose and substitute among different itinerary products that serve the same origin-destination pair. Finding the optimal capacity control and pricing decisions in such problems can be challenging because one needs to simultaneously consider the capacities available to serve a large pool of products. In “An Approximation Algorithm for Network Revenue Management under Nonstationary Arrivals,” Ma, Rusmevichientong, Sumida, and Topaloglu develop efficient methods to make decisions with performance guarantees in high-dimensional capacity control and pricing problems.


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