• 한국경영과학회지
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• 제9권2호
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• pp.15-22
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• 1984

A deterministic multiproduct, facility-in series multiperiod production planning model is analyzed, where each period demand for the product of a facility appear in a fixed proportion of that for the product of the immediately following facility. The model considers concave production and inventory costs, which can depend upon the production in different facilities. No backlogging is allowed. It is shown that the model is represented via a single source network, which facilitates development of efficient dynamic programming algorithms for computing the optimal production schedule.

• 한국산림과학회지
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• 제88권2호
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• pp.273-281
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• 1999

이 연구에서는 춘천국유림관리소 관할인 가리산 일대의 산림을 대상으로 다목적 산림경영을 추구하기 위하여 최적수확계획의 수립에 선형계획법을 적용하였다. 지리적 특성에 따라 연구대상지역을 4개의 경영단위 또는 유역으로 구분하였으며, 비감소수확, 현존 임분의 갱신시기, % 수확면적, 토사유출량, 목재생산량, 탄소저장량을 조절하기 위한 제약조건을 포함하였으며, 계획기간말의 임상구조 및 임분 갱신을 위한 수종선택 조건을 경영단위별로 적용하였다. 선형계획문제의 수식화에는 모델 I과 모델 II를 적용하였으며, 수식모형과 경영대안에 따라 최적해들을 비교검토하였다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.535-538
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• 2006

We consider a two-period airline revenue management problem where customers may act strategically. Specifically, we study a two-fare-class airline seat inventory allocation problem which allow for the possibility that a customer may decide to defer to purchase in the hope that a cheaper ticket than those currently on offer (expensive tickets) become available. We also allow for the possibility that some customer will buy a more expensive ticket if the cheaper tickets are not available. We show how to find the optimal booking limits in the presence of such strategic customer behavior and investigate the impact of such strategic customer behavior on the expected revenue. The results are compared with those by the expected marginal seat revenue (EMSR) heuristic approach (Belobaba, 1987, 1989) with strategic customer behavior.

• 한국경영과학회지
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• 제33권4호
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• pp.53-61
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• 2008

Recently, Ertogral et al.[2] suggested two models considering the transportation cost based on single-vendor single-buyer integrated production-inventory problem. Although their problem-solving algorithm guarantees solutions obtained are optimal, a limitation is revealed that its performance can be inefficient due to complete enumeration search in a certain range. In this paper, a more efficient algorithm in finding optimal solutions is suggested for the same problem suggested by Ertogral et at.[2]. Numerical examples are presented for illustrative purpose.

• 대한안전경영과학회지
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• 제2권3호
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• pp.81-88
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• 2000

In this research, the system is assumed to carry a single item of which the demand types vary. Demand type is defined as a management's classification of the item according to the demand source or to the service purpose. The purpose of this research is to find the optimal inventory control policy when the system carries a single item which consists of multiple demand types. In this research, the optimizing algorithm contains a heuristic, therefore, the optimal is not guaranteed by the algorithm. At least, this research provides the solution to the problems that have not been solved by the existing algorithms.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2000년도 추계학술발표논문집
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• pp.127-130
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• 2000

In this research, the system is assumed to carry a single item of which the demand types vary. Demand type is defined as a management's classification of the item according to the demand source or to the service purpose. The purpose of this research is to find the optimal inventory control policy when the system carries a single item which consists of multiple demand types. In this research, the optimizing algorithm contains a heuristic, therefore, the optimal Is not guaranteed by the algorithm. At least, this research provides the solution to the problems that have not been solved by the existing algorithms.

• 한국철도학회:학술대회논문집
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• 한국철도학회 1998년도 창립기념 춘계학술대회 논문집
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• pp.23-30
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• 1998

The construction of the transportation history database system is to serve the scheduling and seat inventory controling. Recently, lots of countries have been faced with the advance era because of the new railway transportation system, like the high speed railway and/or magnetic levitation vehicle system. This can be reasonably translated as those of operators are willing to provide the more various and high quality schedule to the customer. Those operators' these ideas make possible to forecast that scheduling process is going to be complicated more and more The seat inventory control, so to speak Yield Management System(YMS), goes a long way to improve the total passenger revenue at the railway business. The YMS forecasts the number of the last reservation value(DCP# END) and recommends the optimal values on the seat sales. The history database system contains infra-data(ie, train, seat, sales) that will be the foundation of scheduling and seat inventory control application programs. The development of the application programs are reserved to the next step. The database system is installed on the pc platform(IBM compatible), using the DB2(RDBMS). And at next step, the platform and DBMS will be considered whether they can meet the users' requirement or not.

• 대한안전경영과학회지
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• 제3권3호
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• pp.55-64
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• 2001

The main objective of this research is to develop a model to select the optimal input service level for a distribution center-multi branch inventory distribution system. With the continuous review policy, the distribution center places an order for specific order quantity to an outside supplier, and the order quantity is replenished after a certain lead time Also, each branch places an order for particular order quantity to the distribution center to satisfy the customer demands, and receives the replenishment after a lead time. When an out of stock condition occurs during an order cycle, a backorder is placed to the upper level to fill the unfilled demands. With these situation, variable demand and variable lead time are used for better industrial practice. Further, actual lead times with a generic lead time distribution are used in developing the control model. Under the actual lead time model, the customer service measures actually attained for the distribution center and each branch are explained as the effective customer service measures. Thus, throughout the optimal control (using computer search procedures), we can select the optimal input service levels for the distribution center and each branch to attain the effective service levels for each branch which is consistent with the goal level of service for each branch. At the same time, the entire distribution system keeps minimum inventories.

• Industrial Engineering and Management Systems
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• 제6권2호
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• pp.136-145
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• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

• 대한산업공학회지
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• 제34권1호
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• pp.32-41
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• 2008

This paper studies a joint EOQ and EPQ model in which a stationary demand can be satisfied by recycled products as well as newly purchased products. The model assumes that a fixed quantity of the used products are collected from customers and later recovered for reuse. The recovered products are regarded as perfectly new ones. We also assume that the number of orders for newly purchasing items and the number of recovery setups in a cycle can be mutually independent integers. Under these assumptions, we develop an optimization model obtaining the economic order quantity for newly procured products, the optimal lot size for the recovery process, and the sequence of the orders and the setups, simultaneously. And then a simple solution procedure to find a local optimal control parameter set is proposed. To validate the model and the solution procedure, finally, some computational experiments are presented.