• 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.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.7
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• pp.13-20
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• 2010

Due to the recent quantum leaps forward in bio-, nano-, and information-technologies, the precisionization and miniaturization of mechanical and electrical components are in high demand. The allowable margin for vibration limits for such equipments is becoming stricter. In order to meet this demand, understandings on the characteristics of vibration isolation systems are highly required. Among the components comprising the vibration isolation system, air spring has become a focal point. In order to develop a complex defect tester for COG bonding of display panels, a vibration isolation system composed of air springs for mounting is considered in this study. The dynamic characteristics of the air spring are investigated, which is the most essential ingredient for reducing the vibration problem of the tester to the lowest level. Uncoupled dynamic parameters of the air spring are identified through MTS experiments, followed by suggestion of a model-based approach to obtain the remaining coupled dynamic parameters. Finally, the dynamic behaviors of the air spring are estimated and discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.1-14
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• 1996

We develop a dynamic demand forecasting model compared to regression analysis model and AutoRegressive Integrated Moving Average(ARIMA) model. The dynamic model can apply to the current dynamic data to forecasts through introducing state equation. A multiple regression model and ARIMA model using given data are designed via the model analysis. The forecasting fitness evaluation between the designed models and the dynamic model is compared with the criterion of sum of squared error.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.105-117
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• 2001

This paper models supply uncertainty in the dynamic Newsboy problem context. The system consists of one supplier and one retailer who places an order to the supplier every period to meet stochastic demand. Supply uncertainty is modeled as the uncertainty in quantities delivered by the supplier. That is, the supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of (1-$\beta$). We formulate the problem as a dynamic programming problem and prove that retailer’s optimal replenishment policy is a stationary base-stock policy. Through a numerical study, we found that the cost increase due to supply uncertainty is significant and that the costs increase more rapidly as supply uncertainty increases. We also identified the effects of various system parameters. One of the interesting results is that as retailer’s demand uncertainty, the other uncertainty in our model, increases, the cost increase due to supply uncertainty becomes less significant.

• IE interfaces
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• v.11 no.2
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• pp.13-24
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• 1998

A distribution system is composed of multiple levels from a producer to customers, and it's objective is to supply customers with goods timely with a prescribed level of quality at a minimum cost. For the installation and operation of multi-echelon distribution system, DRP(Distribution Resource Planning) is widely used. However, because of the characteristic difference of material flow dynamic of each distribution center, it is almost impossible to get the optimal distribution scheduling. In this paper, an improved DRP method to schedule multi-echelon distribution network is proposed so that the lot-size and order point is dynamically obtained to meet the change of demand rate and timing. The experiment is done with various demand pattern, forecast errors of demand and lead times of central distribution center. The proposed method is compared with traditional statistical approach.

• 한국IT서비스학회:학술대회논문집
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• 2006.11a
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• pp.360-365
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• 2006

VoD (Video-on-Demand) 서비스는 가입자가 원하는 컨텐츠를 실시간으로 전송하는 서비스의 형태이다. 오늘날은 방대한 양의 멀티미디어 데이터를 효율적으로 압축하고 보다 빠르게 전송할 수 있는 시스템의 발달이 가속화되고 있고 이는 VoD 서비스의 증가로도 이어지고 있다. 그러므로 가입자가 원하는 컨텐츠를 보다 효과적으로 제공할 수 있는 VoD 서비스의 방법을 찾는 것은 중요한 일이다. 본 논문에서는 기존의 NVoD (Near-VoD) 서비스 또는 TVoD (True-VoD) 서비스 만을 제공함으로서 생길 수 있는 단점을 없애고 장점만 살릴 수 있는 방법을 제안하였다. 이는 기존의 가입자단에 Buffer를 제공하여 NVoD를 TVoD화 함으로서 가능하게 하였다. 또한, 본 논문에서 제안한 방법이 필요한 버퍼의 크기를 제시하고 전체적인 알고리즘을 제시하여 이를 구체화 하였다.

• IE interfaces
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• v.17 no.1
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• pp.71-77
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• 2004

At the present time, container transportation plays a key role in the international logistics and the efforts to increase the productivity of container logistics become essential for Korean trucking companies to survive in the domestic as well as global competition. This study suggests an approach for determining fleet size for container road transportation with dynamic demand. Usually the vehicles operated by the transportation trucking companies in Korea can be classified into three types depending on the ways how their expenses occur; company-owned truck, mandated truck which is owned by outsider who entrust the company with its operation, and rented vehicle (outsourcing). Annually the trucking companies should decide how many company-owned and mandated trucks will be operated considering vehicle types and the transportation demands. With the forecasted monthly data for the volume of containers to be transported a year, a heuristic algorithm using tabu search is developed to determine the number of company-owned trucks, mandated trucks, and rented trucks in order to minimize the expected annual operating cost. The idea of the algorithm is based on both the aggregate production planning (APP) and the pickup-and-delivery problem (PDP). Finally the algorithm is tested for the problem how the trucking company determines the fleet size for transporting containers.

• Industrial Engineering and Management Systems
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• v.7 no.3
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• pp.257-265
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• 2008

This paper deals with the joint decisions on pricing and ordering for a monopolistic retailer who sells perishable goods with a fixed lifetime or demand period. The newsvendor-typed problem is formulated as a two-period inventory system where the first period represents the inventory of fresh or new-arrival items and the second period represents the inventory of items that are older but still usable. Demand may be for either fresh items or for somewhat older items that exhibit physical decay or deterioration. The retailer is allowed to adjust the selling price of the deteriorated items in the second period, which stimulates demand and reduces excess season-end or stale inventory. This paper develops a stochastic dynamic programming model that solves the problem of preseason decisions on ordering-pricing and a within-season decision on markdown pricing. We also develop a fixed-price model as a benchmark against the dual-price dynamic model. To illustrate the effect of the dual-price policy on expected profit, we conduct a comparative study between the two models. Extension to a generalized multi-period model is also discussed.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.9
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• pp.433-444
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• 2005

In video-on-demand(VOD) systems, a broadcast-based scheduling mechanism is known to be a very efficient technique for disseminating popular videos to very large client populations. The main motivations of broadcasting scheduling mechanisms are that they scale up extremely well and they have very modest bandwidth requirements. This paper proposes a new dynamic broadcasting scheduling mechanism, named FDBS (fast dynamic broadcasting scheme), and proves its correctness. This paper also evaluates the performance of FDBS on the basis of a simulation approach. The simulation results indicate that FDBS shows a superior performance over UD, CBHD, and NPB in terms of the average response time with very reasonable bandwidth requirements.

• ETRI Journal
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• v.44 no.4
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• pp.624-640
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• 2022

Taxi-demand forecasting and hotspot prediction can be critical in reducing response times and designing a cost effective online taxi-booking model. Taxi demand in a region can be predicted by considering the past demand accumulated in that region over a span of time. However, other covariates-like neighborhood influence, sociodemographic parameters, and point-of-interest data-may also influence the spatiotemporal variation of demand. To study the effects of these covariates, in this paper, we propose three models that consider different covariates in order to select a set of independent variables. These models predict taxi demand in spatial units for a given temporal resolution using linear and ensemble regression. We eventually combine the characteristics (covariates) of each of these models to propose a robust forecasting framework which we call the combined covariates model (CCM). Experimental results show that the CCM performs better than the other models proposed in this paper.