• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.217-228
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• 2009

In this paper, we consider a multi-class queueing system in which different classes of customers have different arrival rates, service rates and class-transition probabilities. We use the fast simulation method to estimate the overflow probability and the expected number of customers of each class at the first time the total number of customers hits a high level. We also discuss the overflow probabilities and the expected number of customers at different loads, respectively.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.4
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• pp.18-26
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• 2006

여러 형태의 고객이 외부로부터 포아송과정에 따라 각 대기행렬에 도착하고 정해진 서비스규칙에 따라 해당 서비스를 받은 후 마코비안 확률분포에 따라 시스템을 떠나거나 다른 형태의 고객으로 시스템을 다시 돌아 올 수도 있는 M/G/1 대기행렬시스템을 고려한다. 본 연구에서는 기존의 연구 모형을 확장하여 계층적 서비스 규칙을 갖는 우선순위 대기행렬모형을 제시하고 이에 대한 시스템 성능척도를 보다 체계적으로 구할 수 있는 방법을 소개한다. 이를 위하여 먼저 대기행렬시스템의 거동을 나타내는 시스템 상태를 정의하고, 바쁜기간과 서비스기간 분석을 통하여 시스템 상태의 선형 함수로 평균체제시간을 구할 수 있음을 보인다.

• Journal of Korean Society of Transportation
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• v.22 no.5
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• pp.123-137
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• 2004

The study on traffic assignment is actively being performed which reflect networks status using time. Its background is increasing social needs to use traffic assignment models in not only hardware area of road network plan but also software area of traffic management or control. In addition, multi-class traffic assignment model is receiving study in order to fill a gap between theory and practice of traffic assignment model. This model is made up of two, one of which is multi-driver class and the other multi-vehicle class. The latter is the more realistic because it can be combined with dynamic model. On this background, this study is to build multidynamic model combining the above-mentioned two areas. This has been a theoretic pillar of ITS in which dynamic user equilibrium assignment model is now made an issue, therefore more realistic dynamic model is expected to be built by combining it with multi-class model. In case of multi-vehicle, FIFO would be violated which is necessary to build the dynamic assignment model. This means that it is impossible to build multi-vehicle dynamic model with the existing dynamic assignment modelling method built under the conditions of FIFO. This study builds dynamic network model which could relieve the FIFO conditions. At the same time, simulation method, one of the existing network loading method, is modified to be applied to this study. Also, as a solution(algorithm) area, time dependent shortest path algorithm which has been modified from existing shortest path algorithm and the existing MSA modified algorithm are built. The convergence of the algorithm is examined which is built by calculating dynamic user equilibrium solution adopting the model and algorithm and grid network.