• 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.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.61-83
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• 2009

This study developed a variable demand traffic assignment model by stable dynamics. Stable dynamics, suggested by Nesterov and do Palma[19], is a new model which describes and provides a stable state of congestion in urban transportation networks. In comparison with the user equilibrium model, which is based on the arc travel time function in analyzing transportation networks, stable dynamics requires few parameters and is coincident with intuitions and observations on congestion. It is therefore expected to be a useful analysis tool for transportation planners. In this study, we generalize the stable dynamics into the model with variable demands. We suggest a three stage optimization model. In the first stage, we introduce critical travel times and dummy links and determine variable demands and link flows by applying an optimization problem to an extended network with the dummy links. Then we determine link travel times and path flows in the following stages. We present a numerical example of the application of the model to a given network.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.167-176
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• 2009

Several travel demand management schemes have been used for controlling overloaded traffics on urban area. To maximize efficiency of the travel management, traffic manager has to set target level that we try to arrive in advance, and then to find optimal variable to attain this goal. In this regard, this paper presents two travel demand management models, expressed by mathematical program, and also presents their solution algorithms. The first is to find optimal travel demand for origin-destination (OD) pair, based on average travel time between the OD pair, and the second is based on the ratio of volume over capacity on congested area. An example is given to test the models.

• Journal of Korean Society of Transportation
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• v.26 no.5
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• pp.163-174
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• 2008

The conventional four-step travel demand model is still widely used as the state-of-practice in most transportation planning agencies even though it does not provide reliable estimates of travel demand. In order to improve the accuracy of travel demand estimation, implementing an alternative approach would be critical as much as acquiring reliable socioeconomic and travel data. Recently, the role of travel demand model is diverse to satisfy the needs of microscopic analysis regarding various policies of travel demand management and traffic operations. In this context, the activity-based approach for travel demand estimation is introduced and a case study of developing a spatial-temporal activity presence-based approach that estimates travel demand through forecasting number of people present at certain place and time is accomplished. Results show that the spatial-temporal activity presence-based approach provides reliable estimates of both number of people present and trips actually people made. It is expected that the proposed approach will provide better estimates and be used in not only long-term transport plans but short-term transport impact studies with respect to various transport policies. Finally, in order to introduce the spatial-temporal activity presence-based approach, the data such as activity-based travel diary and land use based on geographic information system are essential.

• Journal of Korean Society of Transportation
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• v.24 no.6 s.92
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• pp.89-102
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• 2006

The purpose of this paper is to develop a dynamic OD estimating model to overcome the limitation of depicting teal situations in dynamic simulation models based on static OD trip. To estimate dynamic OD matrix we used the hybrid discrete choice model(called the 'Demand Simulation Model'), which combines travel departure time with travel mode and travel path. Using this Demand Simulation Model, we deduced that the traveler chooses the departure time and mode simultaneously, and then choose his/her travel path over the given situation In this paper. we developed a hybrid simulation model by joining a demand simulation model and the supply simulation model (called LiCROSIM-P) which was Previously developed. We simulated the hybrid simulation model for dependent/independent networks which have two origins and one destination. The simulation results showed that AGtt(Average gap expected travel time and simulated travel time) did not converge, but average schedule delay gap converged to a stable state in transportation network consisted of multiple origins and destinations, multiple paths, freeways and some intersections controlled by signal. We present that the hybrid simulation model can estimate dynamic OD and analyze the effectiveness by changing the attributes or the traveler and networks. Thus, the hybrid simulation model can analyze the effectiveness that reflects changing departure times, travel modes and travel paths by demand management Policy, changing network facilities, traffic information supplies. and so on.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.239-242
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• 2003

The supply chain of the airline industry includes multiple airline companies, travel agencies and customers. Various air fares are offered by travel agencies. The travel agencies grant deposit to the airline company in advance and preoccupy seats with deep discount, which called group-discount-ticket. The group-discount-ticket offers the lowest air fare but it does not base on real demand. So the information flow generated by group-discount-ticket can cause the information distortion in airline supply chain. This study analyzes the bullwhip effect in the airline industry. A mathematical model is formulated and managerial suggestions is provided.

• The Journal of the Korea Contents Association
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• v.18 no.3
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• pp.52-61
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• 2018

This research suggested the traffic signal timing calculation model for signal intersections based on sectional travel time. A detection system that collects sectional travel time data such as Urban Transport Information System(UTIS) is applied. This research developed the model to calculate saturation flow rate and demand volume from travel time information using a deterministic delay model. Moreover, this model could determine the traffic signal timings to minimize a delay based on Webster model using traffic demand volume. In micro simulation analysis using VISSIM and its API ComInterface, it checked the saturation conditions and determined the traffic signal timings to minimize the intersection delay. Recently, sectional vehicle detection systems are being installed in various projects, such as Urban Transportation Information System(UTIS) and Advanced Transportation Management System(ATMS) in Korea. This research has important contribution to apply the traffic information system to traffic signal operation sector.

• Health Policy and Management
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• v.8 no.1
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• pp.183-202
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• 1998

This study is to investigate patient's choice of health care and the demand for Korean traditional medicine care in rural areas in 1995. It tried to evaluate the effect of out-of-pocket expenditure, travel time, and waiting time on improving care-seeking and substituting clinical medicine for pharmacy care and Korean traditional medicine care in rural areas. The statistical model of this study is conditional logit to estimate effects of choice-specific and individual-specific characteristics on the choice of type of services. This study used, as explanatory variables, average out-of-pocket payment, travel time, and waiting time of services required to use the services. The model was empirically tested using data from 1995 Korean National Health Survery. The results showed that rural Koreans responded to out-of pocket payment and travel time. Increases of out-of-pocket payment and travel time decreased the probability to choose care in rural Korea. Rural Koreans were more likely to seek care than others with low out-of-pocket payment and travel time. The probability of choosing Korean traditional medicine were higher among the members of the households with higher education level and older persons, while they were lower in the households with large family than others compared with the probabilities of choosing public health facilities. The result of this study implies that policy on use of health care in rural Korea can be focused in managing travel time and out-of-pocket payment.

• Korean Management Science Review
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• v.17 no.2
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• pp.87-95
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• 2000

This paper presents two analytical approaches to determine the vehicle fleet size for container shuttle service. The shuttle service can be defined as the repetitive travel between the designated places during working period. In the first approach, the transportation model is adopted in order to determine the number of vehicles required. Its advantages and disadvantages in practical application are also discussed. In the second approach, a logical network which is oriented on job is transformed from a physical network which is focused on demand site. Nodes on the logical network represent jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next job. Then a mathematical formulation is constructed similar to the multiple traveling salesman problem (TSP). A solution procedure is carried out based on the well-known insertion heuristic with the real world data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.17-34
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• 2022

This paper develops a model for dynamic station assignment to optimize the Demand Responsive Transit (DRT) operation. In the process of optimization, we use the bus travel time as a variable for DRT management. In addition, walking time, waiting time, and delay due to detour to take other passengers (detour time) are added as optimization variables and entered for each DRT passenger. Based on a network around Anaheim, California, reserved origins and destinations of passengers are assigned to each demand responsive bus, using K-means clustering. We create a model for selecting the dynamic station and bus route and use Non-dominated Sorting Genetic Algorithm-III to analyze seven scenarios composed combination of the variables. The result of the study concluded that if the DRT operation is optimized for the DRT management, then the bus travel time and waiting time should be considered in the optimization. Moreover, it was concluded that the bus travel time, walking time, and detour time are required for the passenger.