Seat Inventory Control for Network-based Revenue Management Systems

2016 ◽  
pp. 201-216
Keyword(s):  
Revenue Management ◽  
Inventory Control ◽  
Management Systems ◽  
Seat Inventory Control

A Model for Seat Allocation of Railway Passenger Transport Based on OD’s Priority

2014 ◽  
Vol 989-994 ◽  
pp. 2344-2348 ◽  
Author(s):  
Ying Ting Zhu ◽  
Fu Zhang Wang ◽  
Xing Hua Shan ◽  
Xiao Yan Lv
Keyword(s):  
Revenue Management ◽  
Inventory Control ◽  
Optimization Model ◽  
Control Method ◽  
Optimization Strategy ◽  
Passenger Transport ◽  
Railway Passenger Transport ◽  
Seat Allocation ◽  
Railway Passenger ◽  
Seat Inventory Control

Based on the seat inventory control method of revenue management in airline, the author researches the optimization strategy on the seat inventory control in railway passenger transport. The author proposes one optimization model for seats allocation, which is to allocate seats by calculating the value to determine the order of getting seats for each OD under the analysis of the interaction among all trains running on the same rail lines and those trains’ demands intensity. The experiment results show that this new model can be used to allocate seats for the train with multiple stations rapidly and appropriately. In comparison with the method without considering the value of each OD, the model based on OD’s value can get better results.

Airline Revenue Management: Optimization Using Origin-Destination Strategy Controlled by Nested Heuristics

2012 ◽  
Vol 229-231 ◽  
pp. 2775-2778
Author(s):  
Ajyuk J. Raj ◽  
Ganesh Kumar Nithyanandam ◽  
S. Jayaraj
Keyword(s):  
Revenue Management ◽  
Inventory Control ◽  
Accurate Result ◽  
Management Practice ◽  
Control Process ◽  
Linear Program ◽  
Airline Revenue Management ◽  
The Difference ◽  
Management Optimization ◽  
Seat Inventory Control

Effective revenue management practice can be the single most important factor in distinguishing between success and failure of an airline and spell the difference between profitability and loss for a particular flight. This paper deals with usage of Deterministic Linear Program to optimize the network as a whole and uses LINGO to solve the DLP as it has 120 variables and 127 constraints and is impossible to solve manually. Optimization strategies taken into consideration are: Leg Based Expected Margins, Seat Revenue (EMSR), and Deterministic Linear Program (DLP). In the seat inventory control process Nested Heuristics is used for an improved and accurate result.

scholarly journals MILP Model For Network Revenue Management In Airlines

2010 ◽  
Vol 8 (2) ◽  
Author(s):  
Yoon Sook Song ◽  
Seong Tae Hong ◽  
Myung Sun Hwang ◽  
Moon Gil Yoon
Keyword(s):  
Revenue Management ◽  
Inventory Control ◽  
Optimal Solution ◽  
Approximation Technique ◽  
Stochastic Programs ◽  
Booking Limits ◽  
Bid Price ◽  
Dynamic Stochastic ◽  
Inventory Control Problem ◽  
Seat Inventory Control

<p class="MsoNormal" style="text-justify: inter-ideograph; text-align: justify; margin: 0in 36.1pt 0pt 0.5in; layout-grid-mode: char;"><span style="mso-bidi-font-style: italic;"><span style="font-size: x-small;"><span style="font-family: Times New Roman;">Seat inventory control is an important problem in revenue management which is to decide whether to accept or reject a booking request during the booking horizon in airlines. The problem can be modeled as dynamic stochastic programs, which are computationally intractable in network settings. Various researches have been tried to solve it effectively. Even though dynamic (and stochastic) programming (DP) models can be solved it optimally, they are computationally intractable even for small sized networks. Therefore, in practice, DP models are approximated by various mathematical programming models. In this paper, we propose an approximation model for solving airline seat inventory control problem in network environments. Using Linear Approximation technique, we will transform our problem into a concave piecewise LP model. Based on the optimal solution of ours, we suggest how to implement it for airline inventory control policies such as booking limits, bid-price controls and virtual nesting controls.</span></span></span></p>

scholarly journals A Welfare Assessment of Revenue Management Systems

2020 ◽  
Vol 19 (1) ◽  
pp. 1-41
Author(s):  
Nicolas Dupuis ◽  
Marc Ivaldi ◽  
Jerome Pouyet
Keyword(s):  
Theoretical Model ◽  
Revenue Management ◽  
Consumer Preferences ◽  
Consumer Surplus ◽  
Capacity Constraints ◽  
Management Systems ◽  
Optimal Pricing ◽  
Pricing Strategies ◽  
Welfare Impact ◽  
Welfare Assessment

AbstractWe study the welfare impact of revenue management, a practice which is widely spread in the transport industry, but whose impact on consumer surplus remains unclear. We develop a theoretical model of revenue management allowing for heterogeneity in product characteristics, capacity constraints, consumer preferences, and probabilities of arrival. We also introduce dynamic competition between revenue managers. We solve this model computationally and recover the optimal pricing strategies. We find that revenue management is generally welfare enhancing as it raises the number of sales.

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