• Structural Engineering and Mechanics
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• 제17권3_4호
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• pp.281-290
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• 2004

A review of current procedures being used in engineering practice to analyze the response of structure/foundation systems subjected separately to different types of dynamic excitation, such as earthquake, sea-wave action, wind, or moving wheel loads, is presented. Separate formulations are given for analyzing systems in the time and frequency domains. Both deterministic and stochastic forms of excitation are treated. A distinction is made between demand and capacity analyses.

• 한국경영과학회지
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• 제12권2호
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• pp.5-20
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• 1987

This paper addresses sensitivity analysis for a deterministic multi-period production and inventory model. The model assumes a piecewise linear cost structure, but permits backlogging of unsatisfied demand. Our approach to sensitivity analysis here can be divided into two basic steps; (1) to find the optimal production policy through a forward dynamic programming algorithm similar to the backward version of Zangwill [1966] and (2) to apply the penalty network approach by the author [1986] in order to derive sensitivity ranges for various model parameters. Computational aspects are discussed and topics of further research are suggested.

• 한국국방경영분석학회지
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• 제9권1호
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• pp.69-74
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• 1983

This article presents a deterministic inventory model for situations in which, during the stockout period, a fraction ${\beta}$ of the demand is backordered and the remaining fraction $1-{\beta}$ is lost. By defining a time proportional backorder cost and a fixed penalty cost per unit lost, a convex objective function representing the average annual cost of operating the inventory system is obtained. The optimal operating policy variables are calculated directly. At the extremes ${\beta}\;=\;1$ and ${\beta}\;=\;0$ the model presented reduces to the usual backorders and lost sales case, respectively.

• 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.

• 대한산업공학회지
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• 제13권2호
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• pp.1-8
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• 1987

In this paper, a deterministic EOQ model with interest rate in which a proportion (${\beta}$) of the demand is backlogged and the rest (1-${\beta}$) is lost. The optimal order quantity is derived and the corresponding average cost is obtained, Sensitivity analysis is performed to sec the influence of interest rate on the optimal order quantity and the average cost. Finally a numerical example is given in which optimum quantities of the model developed in this study and those of the conventional EOQ model are compared.

• 산업경영시스템학회지
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• 제8권12호
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• pp.89-95
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• 1985

MRP System에서 시스템 성능을 향상시킬 수 있는 하나의 인자는 우수한 Lot-Sizing rule의 선택과 발견이다. 널리 사용되고 있는 Lot-Sizing rule 들 중 Wagner-Whitin 알고리즘은 생산준비 비용과 재고 유지비용이 가변적일 경우 동적 로트크기 결정에 우수한 forward 알고리즘이다. 본 연구에서는 Wagner-Whitin 알고리즘의 중요 원리들을 응용하여 LDS 알고리즘이라 명명한 backward 알고리즘을 개발한다. 그리고 개발된 알고리즘을 Wagner-Whitin 알고리즘과 비교함으로 그 유효성을 테스트하고 backward 알고리즘이 가지는 계산상의 장점을 고찰한다.

• 한국경영과학회지
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• 제25권4호
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• pp.111-122
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• 2000

This paper considers remanufacturing planning problems under deterministic environments. As increasing the environmental pressures in manufacturing, various methods for reducing wasted or postponing the time to be waste are considered. This paper considers remanufacturing planning problems on a single facility, where the wastes(or used products) are remanufactured to satisfy the given demand on the remanufactured products. The objective is to find the optimal remanufacturing and purchasing planning of the wastes which minimize total cost subject to satisfaction all the given demand on the remanufactured products. Two problems that the amount of wastes is a given constant or a decision variable are considered, respectively. For the problems, the extreme point solutions are characterized, and dynamic programming algorithms are developed with numerical examples.

• 경영과학
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• 제32권1호
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• pp.65-82
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• 2015

Purchase dependence is a frequent phenomenon in retail shops and is characterized by the purchase of certain items together due to their unknown interior associations. Although this concept has been significantly examined in the marketing field (e.g. market basket analysis), it has largely remained unaddressed in operations management. Since purchase dependence is an important factor in designing inventory replenishment policies, this paper demonstrates the means of applying it to the partial backordering inventory model. Through computational analyses, this paper compares the performance of inventory models that either consider or ignore purchase dependence; the results demonstrate that inventory models that ignore purchase dependence incur more average cost per unit time than the model that considers purchase dependence, and the impact of purchase dependence can increase in significance as the item set becomes more closely correlated with regard to order demand.

• 대한산업공학회지
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• 제12권2호
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• pp.77-87
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• 1986

This paper presents a heuristic method for solving the discrete-time ordering problem with quantity discounts and deterministic, time-varying demand. This algorithm utilizes a variation of the incremental cost approach(ICA) to determine a near optimal solution. The ICA is the method which reduces the total cost with reduction of the number of orders by one. In order to reduce the number of orders, if the incremental cost for one of the periods is negative, the demand of the period should be purchased in its immediate preceding period. In order to test the performance of this algorithm, an experiment is conducted that involves a large number of test problems covering a wide variety of situations. The result of the experiment shows that the proposed algorithm has 80.5% better solutions than the adjusted part period algorithm(APPA), which is known to be the best heuristic method.

• Industrial Engineering and Management Systems
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• 제16권1호
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• pp.44-51
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• 2017

In today's competitive environment, supply chain management is a major concern for a company. Two of the key issues in supply chain management are transportation and inventory management. To achieve significant savings, companies should integrate these two issues instead of treating them separately. In this paper we develop a framework for modeling stochastic programming in a supply chain that is subject to demand uncertainty. With reasonable assumptions, two stochastic programming models are presented, respectively, including a single-period and a multi-period situations. Our assumptions allow us to capture the stochastic nature of the problem and translate it into a deterministic model. And then, based on the genetic algorithm and stochastic simulation, a solution method is developed to solve the model. Finally, the computational results are provided to demonstrate the effectiveness of our model and algorithm.