• 경영과학
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• 제25권1호
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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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2008년도 추계학술대회 및 정기총회
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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.

• 경영과학
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• 제26권3호
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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.

• 한국콘텐츠학회논문지
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• 제7권5호
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• pp.156-165
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• 2007

최근 수입경영은 항공운송산업뿐만 아니라 이와 유사한 일회성상품(perishable assets)의 성격을 갖는 산업 전 부문에서 널리 활용되고 있다. 본 논문은 항공산업에서 활용되고 있는 정태적 좌석할당모형을 기반으로 시점마다 무작위로 발생하는 고 저가의 항공수요가 각 요금수준별 사전 할당된 좌석의 유무에 상관없이 필요에 따라 상하 이동을 하며 고가수요가 저가의 좌석을 선택할 수도, 저가의 수요가 고가의 좌석을 구입할 수도 있다는 전제로 기존의 한 방향 좌석할당모형과 대별되는 양방향 좌석할당모형을 개발한다. 또한 본 모형을 기반으로 항공사 수입이 기존의 한 방향 수요이동을 고려한 모형과 비교하여 수입을 더욱 극대화 시킬 수 있다는 사실을 실증한다. 실증방법은 C-프로그램을 활용하여, 수요의 가격수준을 국내 K항공사에서 한국지역 판매를 위해 활용되고 있는 4가지 운임으로 구분하고, 수요분포는 최대값과 최소값을 발생확률에 따라 난수를 이용하게 되며, 요금수준은 한국지역의 요금수준분포를 참조하여 고가를 100, 90, 85, 80 수준으로 하여 모의실험을 시행한다. 그 결과 고가의 수요에 지나친 좌석할당을 시행하는 경우를 제외하고는 수요의 양방향을 고려한 항공좌석할당 방법이 높은 수준의 수입을 창출할 수 있다는 결론을 얻게 된다.

• 한국철도학회논문집
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• 제8권6호
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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.