• Korean Management Science Review
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• v.25 no.1
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• pp.93-106
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• 2008

This study is focused on the problem of seat allocation for group travel demand in airlines. We first explain the characteristic of group demand and its seat allocation process. The group demand in air travel markets can be classified into two types : incentive and package groups. Allocating seats for group demand depends on the types of group demand and the relationship between airlines and travel agents. In this paper we concentrate on the package group demand and develop an optimization model for seat allocation on the demand to maximize the total revenue. With some assumptions on the demand distribution and the linear approximation technique, we develop a mixed IP model for solving our problem optimally. From the computational experiments, we can find our optimization model can be applied well for real-world application.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.65-75
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• 2008

Over the last three decades, there are many researches focusing on the practice and theory of RM in airlines. Most of them have dealt with a seat assignment problem for maximizing the total revenue. In this study, we focus on a seat assignment problem in airlines. The seat assignment problem can be modeled as a stochastic programming model which is difficulty to solve optimally. However, with some assumptions on the demand distribution functions and a linear approximation technique, we can transform the complex stochastic programming model to a Linear Programming model. Some computational experiments are performed to evaluate out model with randomly generated data. They show that our model has a good performance comparing to existing models, and can be considered as a basis for further studies on improving existing seat assignment models.

• Korean Management Science Review
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• v.26 no.3
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• pp.117-131
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• 2009

Over the last three decades, there are many researches focusing on the practice and theory of RM in airlines. Most of them have dealt with a seat assignment problem for maximizing the total revenue. In this study, we focus on a seat assignment problem in airlines. The seat assignment problem can be modeled as a stochastic programming model which is difficulty to solve optimally. However, with some assumptions on the demand distribution functions and a linear approximation technique, we can transform the complex stochastic programming model to a Linear Programming model. Some computational experiments are performed to evaluate out model with randomly generated data. They show that our model has a good performance comparing to existing models, and can be considered as a basis for further studies on improving existing seat assignment models.

• The Journal of the Korea Contents Association
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• v.7 no.5
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• pp.156-165
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• 2007

The concepts of static seat allocation model has been used widely in the air transportation industry, and proven as a good concepts for managing perishable assets. The paper analyzed, in realistic environment, the volume of Accept Demand and Reject Demand through several times' simulation experiments at each fare level by using C-Program analyzing process applied to upward and downward models of demand, to analyze the change of fare level when upward and downward shifts of fare levels' demand happen at once. As a consequence, I concluded that the revenue of the case to consider the both shifts of demand at each fare level is bigger than that of the case to consider the single shift of demand at each fare level, except the case to downsize the seat allotment at very low price when supply is bigger than demand, with developing a general model concerned with plural fare levels.

• Journal of the Korean Society for Railway
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• v.8 no.6 s.31
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• pp.602-609
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• 2005

In this paper, we consider the train-fleet assignment problem to determine fleet assignment and seat allocation synchronously. An integer programming model of the problem and a decomposition-based solution approach are developed to handle short-term period deterministic orgin-destination demands. The primary objective used in the developed model is to maximize the total number of passengers transported during peak load periods, such as Chuseok national holiday period. Thus, in developing the model we choose to profit-pursuing system. We also show how the proposed model can be readily modified to incorporate profit-maximization. Using the empirical data sets provided by a Korean railroad company, we have tested the proposed solution approach and carried out various comparison analyses by varying traffic demand patterns and train schedules. The computational experiments reveal that the proposed solutions approach produces high quality solutions in reasonable computation time.