• 한국항만경제학회지
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• 제25권4호
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• pp.183-202
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• 2009

본 연구는 1단계로 우리나라 무역항의 대기비용을 장기기회비용관점에서 산정하였다. 2단계로 이를 활용한 선박당 평균 대기비용을 활용하여 항만의 서비스 수준을 평가하는 방법을 제시하였다. 항만대기비용은 사회적 비용을 반영하기 때문에 특정 항만의 시설확충여부에 대한 의사결정지원 정보이지만 서비스지표로는 활용되기 어렵다. 또한 대기척수비율이나 대기시간비율도 시간기준의 양적 측면만을 반영한 불충분한 지표였다. 그러나 본 연구에서 제시한 선박당 평균대기비용은 대기시간과 선박 및 화물의 경제적 가치 손실을 동시에 반영하는 항만 서비스수준의 평가지표로 활용할 수 있다. 화주나 선사가 항만을 선택하는 과정에서도 매우 유용한 정보이다. 2007년 선박당 대기비용 기준으로 서비스 수준이 낮은 항만은 평택당진, 포항, 동해, 삼천포 순으로 분석되었다. 이는 항만 대기비용 관점의 포항, 인천, 광양, 평택당진, 울산 순서와는 다른 것이다. 항만 대기비용이 항만 관리자에게 중요한 지표라면 선박당 대기비용은 항만 이용자의 관점에서 항만별 서비스 수준을 평가할 수 있는 유용한 지표이다.

• 해양환경안전학회지
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• 제25권1호
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• pp.27-33
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• 2019

북베트남의 컨테이너 터미널을 주제로 한 연구는 다수 있지만, 선박의 대기시간이나 화물처리에 관련한 비용 측면에서의 경쟁을 다룬 연구는 거의 없다. 이 논문은 북 베트남에 입지한 컨테이너 터미널의 TEU당 평균대기비용을 추산해 본 연구다. 우선 대기행렬이론을 적용하여 평균대기시간을 추산한 뒤, 불확실성 이론을 적용하여 선박의 일당 비용을 추산할 것이다. 그리고 각 터미널의 하역능력 내지 물동량 처리율과 관련하여 TEU당 일련의 대기시간을 산정하기 위해 시뮬레이션을 실시하였다. 추산된 일련의 대기시간을 근거로 하여 각 항만의 평균대기시간과 물동량 처리율 / 하역률 간의 관계를 제시하기 위한 함수를 추정하기 위해 비선형회귀법을 적용하였다. 연구 결과는 북베트남의 컨테이너 터미널간의 경쟁상황에 관한 후속 연구에서 게임이론을 적용하는 데 이용될 수 있을 것이다.

• International Journal of Reliability and Applications
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• 제3권4호
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• pp.165-171
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• 2002

An optimization of the M/M/1 queue with impatient customers is studied. The impatient customer does not enter the system if his or her virtual waiting time exceeds the threshold K ＞ 0. After assigning three costs to the system, a cost proportional to the virtual waiting time, a penalty to each impatient customer, and also a penalty to each unit of the idle period of the server, we show that there exists a threshold K which minimizes the long-run average cost per unit time.

• 한국컴퓨터정보학회논문지
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• 제23권8호
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• pp.133-142
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• 2018

Subway metro scheduling is one of the most important problems impacting passenger convenience today. To operate efficiently, the Seoul metro uses regular, periodic schedules for all lanes, both north and southbound. However, many past studies suggest that non-periodic scheduling would better optimize costs. Since the Seoul metro is continuously facing a deficit, adopting a non-periodic schedule may be necessary. Two objectives are presented; the first, to minimize the average passengers' waiting time, and the second, to minimize total costs, the sum of the passenger waiting time, and the operational costs. In this paper, we use passenger smart card data and a precise estimation of transfer times. To find the optimal time-table, a genetic algorithm is used to find the best solution for both objectives. Using Python 3.5 for the analysis, for the first objective, we are able to reduce the average waiting time, even when there are fewer trains. For the second objective, we are able to save about 4.5 thousand USD with six fewer trains.

• 자원ㆍ환경경제연구
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• 제11권4호
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• pp.659-687
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• 2002

This study used a discrete choice model to investigate an association between air pollution and hospital visits for acute respiratory symptoms with the national health interview survey conducted in 1998 in South Korea. The results showed that $NO_2$ and TSP were significantly related to hospital visits in a single-pollutant model, but when they were simultaneously considered, only $NO_2$ remained significant. It was estimated as $NO_2$ level increased by 10%(0.0027ppm) from 0.027ppm (the mean $NO_2$ level), hospital visits increase by 0.176%. This study also measured respondent's out-of-pocket expense and the time cost for commuting and waiting for the visit. We found that on the average, out-of-pocket expense is 5,600 won per hospital visit, but the total cost per hospital visit is measured at 33,440 won with time cost of commuting and waiting at 27,840 won. Time cost was over 63.6~83.3% of the total cost per hospital visit.

• 산업공학
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• 제13권3호
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• pp.424-430
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• 2000

Supply chain management (SCM) is an area that has recently received a great deal of attention in the business community. While SCM is relatively new, the idea of coordinated planning is not. During the last decades, many researchers have investigated multi-stage inventory problems. However, only a few papers address the problem of cost-optimal coordination of multi-stage inventory control with respect to service measures. Even published approaches have a shortcoming in dealing with a delivery lead time consisted of a shipping time and a waiting time. Assumed that there is no waiting time, or that the delivery lead time is implicitly compounded of a shipping time and a waiting time, the problem is often simplified into a multi-stage buffer allocation and a single-stage stochastic buffer sizing problem at all installations. This paper presents a simulation-based heuristic algorithm and a comparison with others for the problem that cannot be decomposed into a multi-stage buffer allocation and a single-stage stochastic buffer sizing problem because the waiting time ties together all stages. The comparison shows that the simulation-based heuristic algorithm performs better than other approaches in saving average inventory cost for both Poisson and Normal demands.

• 한국항만학회지
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• 제5권2호
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• pp.19-37
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• 1991

This work aims to : establish a model of the container physical distribution system of Pusan port comprising 4 sub-systems of a navigational system, on-dock cargo handling/transfer/storage system, off-dock CY system and an in-land transport system : examine the system regarding the cargo handling capability of the port and analyse the cost of the physical distribution system. The overall findings are as follows : Firstly in the navigational system, average tonnage of the ships visiting the Busan container terminal was 33,055 GRT in 1990. The distribution of the arrival intervals of the ships' arriving at BCTOC was exponential distribution of $Y=e^{-x/5.52}$ with 95% confidence, whereas that of the ships service time was Erlangian distribution(K=4) with 95% confidence, Ships' arrival and service pattern at the terminal, therefore, was Poisson Input Erlangian Service, and ships' average waiting times was 28.55 hours In this case 8berths were required for the arriving ships to wait less than one hour. Secondly an annual container through put that can be handled by the 9cranes at the terminal was found to be 683,000 TEU in case ships waiting time is one hour and 806,000 TEU in case ships waiting is 2 hours in-port transfer capability was 913,000 TEU when berth occupancy rate(9) was 0.5. This means that there was heavy congestion in the port when considering the fact that a total amount of 1,300,000 TEU was handled in the terminal in 1990. Thirdly when the cost of port congestion was not considered optimum cargo volume to be handled by a ship at a time was 235.7 VAN. When the ships' waiting time was set at 1 hour, optimum annual cargo handling capacity at the terminal was calculated to be 386,070 VAN(609,990 TEU), whereas when the ships' waiting time was set at 2 hours, it was calculated to be 467,738 VAN(739,027 TEU). Fourthly, when the cost of port congestion was considered optimum cargo volume to be handled by a ship at a time was 314.5 VAN. When the ships' waiting time was set at I hour optimum annual cargo handling capacity at the terminal was calculated to be 388.416(613.697 TEU), whereas when the ships' waiting time was set 2 hours, it was calculated to be 462,381 VAN(730,562 TEU).

• 산업경영시스템학회지
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• 제20권43호
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• pp.153-162
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• 1997

M/G/1 queueing system is one of the most widely used one to model the real system. When operating a real systems, since it often takes cost, some control policies that change the operation scheme are adopted. In particular, the N-policy is the most popular among many control policies. Almost all researches on queueing system are based on the assumption that the arrival rates of customers into the queueing system is constant, In this paper, we consider the M/G/1 queueing system whose arrival rate varies according to the servers status : idle, set-up and busy states. For this study, we construct the steady state equations of queue lengths by means of the supplementary variable method, and derive the PGF(probability generating function) of them. The L-S-T(Laplace Stieltjes transform) of waiting time and average waiting time are also presented. We also develop an algorithm to find the optimal N-value from which the server starts his set-up. An analysis on the performance measures to minimize total operation cost of queueing system is included. We finally investigate the behavior of system operation cost as the optimal N and arrival rate change by a numerical study.

• 물과 미래
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• 제12권1호
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• pp.60-71
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• 1979

In general, the lock structure is built at place of having great deal range for dealing with effective ships operation such as in the west coast of Korea. In Inchon harbour, the two locks of 10 KT and 50 KT tonnage class in total has been constructed for several years age, however, it has been recorded many waiting vessels at outer harbour due to the increment of oceangoing vessels & shortage of berthing facilities in accordance with beyond expectation of cargo amount increment. This paper attempts to solves the waiting vessels problem at outer harbour by simulation in applying queing theory. It is found that the simulation results such as average queue time, service time, and queue length during lock operation can be applied to find the minimum of the cost function for determination of optimum Lock Size

• 산업경영시스템학회지
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• 제39권3호
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• pp.147-155
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• 2016

Industry 4.0's goal is the 'Smart Factory' that integrates and controls production process, procurement, distribution and service based on the fundamental technology such as internet of the things, cyber physical system, sensor, etc. Basic requirement for successful promotion of this Industry 4.0 is the large supply of semiconductor. However, company I who produces dicing blades has difficulty to meet the increasing demand and has hard time to increase revenue because its raw material includes high price diamond, and requires very complex and sensitive process for production. Therefore, this study is focused on understanding the problems and presenting optimal plan to increase productivity of dicing blade manufacturing processes. We carried out a study as follows to accomplish the above purposes. First, previous researches were investigated. Second, the bottlenecks in manufacturing processes were identified using simulation tool (Arena 14.3). Third, we calculate investment amount according to added equipments purchase and perform economic analysis according to cost and sales increase. Finally, we derive optimum plan for productivity improvement and analyze its expected effect. To summarize these results as follows : First, daily average blade production volume can be increased two times from 60 ea. to 120 ea. by performing mixing job in the day before. Second, work flow can be smoother due to reduced waiting time if more machines are added to improve setting process. It was found that average waiting time of 23 minutes can be reduced to around 9 minutes from current process. Third, it was found through simulation that the whole processing line can compose smoother production line by performing mixing process in advance, and add setting and sintering machines. In the course of this study, it was found that adding more machines to reduce waiting time is not the best alternative.