• 제목/요약/키워드: dynamic lot sizing problem

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확률적 수요를 갖는 단일설비 다종제품의 동적 생산계획에 관한 연구 (A Study on Dynamic Lot Sizing Problem with Random Demand)

  • 김창현
    • 대한산업공학회지
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    • 제31권3호
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    • pp.194-200
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    • 2005
  • A stochastic dynamic lot sizing problem for multi-item is suggested in the case that the distribution of the cumulative demand is known over finite planning horizons and all unsatisfied demand is fully backlogged. Each item is produced simultaneously at a variable ratio of input resources employed whenever setup is incurred. A dynamic programming algorithm is proposed to find the optimal production policy, which resembles the Wagner-Whitin algorithm for the deterministic case problem but with some additional feasibility constraints.

최소공급량 정책을 위한 추후조달 롯사이징 문제 (A Dynamic Lot-Sizing Problem with Backlogging for Minimum Replenishment Policy)

  • 황학진
    • 대한산업공학회지
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    • 제36권1호
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    • pp.7-12
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    • 2010
  • This paper considers a dynamic lot-sizing problem with backlogging under a minimum replenishment policy. For general concave production costs, we propose an O($T^5$) dynamic programming algorithm. If speculative motive is not allowed, in this case, a more efficient O($T^4$) algorithm is developed.

생산용량 제약하의 2 단계 공급체인에 대한 효율적인 롯사이징 알고리듬 (An Improved Algorithm for a Capacitated Dynamic Lot-Sizing Problem with Two-Stage Supply Chain)

  • Hwang, Hark-Chin
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2008년도 추계학술대회 및 정기총회
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    • pp.290-296
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    • 2008
  • This paper considers a two-stage dynamic lot-sizing problem constrained by a supplier's production capacity. We derive an improved O($T^6$) algorithm over the O($T^7$) algorithm in van Hoesel et al. (2005).

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납품시간창과 다종의 컨테이너를 고려한 동적 로트크기결정 및 아웃바운드 디스패칭 문제 (A Dynamic Lot-Sizing and Outbound Dispatching Problem with Delivery Time Windows and Heterogeneous Container Types)

  • 서원철;이운식
    • 대한산업공학회지
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    • 제40권4호
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    • pp.435-441
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    • 2014
  • This paper considers a single-product problem for inbound lot-sizing and outbound dispatching at a third-party warehouse, where the demand is dynamic over the discrete time horizon. Each demand must be delivered into the corresponding delivery time window which is the time interval characterized by the earliest and latest delivery dates of the demand. Ordered products are shipped by heterogeneous container types. Each container type has type-dependent carrying capacity and the unit freight cost depends on each container type. Total freight cost is proportional to the number of each container type used. Also it is assumed that related cost functions are concave and backlogging is not allowed. The objective of the paper is to simultaneously determine the optimal inbound lot-sizing and outbound dispatching plans that minimize total costs which include ordering, shipping, and inventory holding costs. The optimal solution properties are characterized for the problem and then a dynamic programming algorithm is presented to find the optimal solution.

다종제품 동적로트사이징에 관한 연구 (A Study on Multiple Product Dynamic Lot-sizing)

  • 강용하
    • 한국산학기술학회논문지
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    • 제13권7호
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    • pp.2955-2963
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    • 2012
  • 본 논문은 다품종 동적 로트사이징 문제를 풀기 위하여 열생성 기법에 기반한 알고리즘을 제안한다. 제안한 알고리즘의 기본 개념은 한정된 생산 용량을 주문제를 통하여 n개의 제품에 할당하고, 주문제에 의하여 할당된 생산용량을 기반으로 하여 각각의 제품에 대하여 최적화된 로트사이징 문제를 반복적으로 풀어나감으로써 해를 구해나가는 것이다. 부문제를 풀기 위해 본 논문은 로트사이즈, 재공재고 그리고 생산량 간에 존재하는 비선형관계를 기반으로 한 M/G/1모델 기반의 최적화 로트사이징 모델을 제안한다. 실험을 통하여 제안한 알고리즘이 비교적 짧은 시간안에 좋은 해를 생성함을 보여준다.

Meta-Heuristic Algorithms for a Multi-Product Dynamic Lot-Sizing Problem with a Freight Container Cost

  • Kim, Byung-Soo;Lee, Woon-Seek
    • Industrial Engineering and Management Systems
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    • 제11권3호
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    • pp.288-298
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    • 2012
  • Lot sizing and shipment scheduling are two interrelated decisions made by a manufacturing plant and a third-party logistics distribution center. This paper analyzes a dynamic inbound ordering problem and shipment problem with a freight container cost, in which the order size of multiple products and single container type are simultaneously considered. In the problem, each ordered product placed in a period is immediately shipped by some freight containers in the period, and the total freight cost is proportional to the number of containers employed. It is assumed that the load size of each product is equal and backlogging is not allowed. The objective of this study is to simultaneously determine the lot-sizes and the shipment schedule that minimize the total costs, which consist of production cost, inventory holding cost, and freight cost. Because the problem is NP-hard, we propose three meta-heuristic algorithms: a simulated annealing algorithm, a genetic algorithm, and a new population-based evolutionary meta-heuristic called self-evolution algorithm. The performance of the meta-heuristic algorithms is compared with a local search heuristic proposed by the previous paper in terms of the average deviation from the optimal solution in small size problems and the average deviation from the best one among the replications of the meta-heuristic algorithms in large size problems.

다종의 차량과 납품시간창을 고려한 동적 로트크기 결정 및 디스패칭 문제를 위한 자율유전알고리즘 (An Adaptive Genetic Algorithm for a Dynamic Lot-sizing and Dispatching Problem with Multiple Vehicle Types and Delivery Time Windows)

  • 김병수;이운식
    • 대한산업공학회지
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    • 제37권4호
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    • pp.331-341
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    • 2011
  • This paper considers an inbound lot-sizing and outbound dispatching problem for a single product in a thirdparty logistics (3PL) distribution center. Demands are dynamic and finite over the discrete time horizon, and moreover, each demand has a delivery time window which is the time interval with the dates between the earliest and the latest delivery dates All the product amounts must be delivered to the customer in the time window. Ordered products are shipped by multiple vehicle types and the freight cost is proportional to the vehicle-types and the number of vehicles used. First, we formulate a mixed integer programming model. Since it is difficult to solve the model as the size of real problem being very large, we design a conventional genetic algorithm with a local search heuristic (HGA) and an improved genetic algorithm called adaptive genetic algorithm (AGA). AGA spontaneously adjusts crossover and mutation rate depending upon the status of current population. Finally, we conduct some computational experiments to evaluate the performance of AGA with HGA.

반도체 생산 배취공정에서의 배취 크기의 결정 (Batch Sizing Heuristic for Batch Processing Workstations in Semiconductor Manufacturing)

  • 천길웅;홍유신
    • 대한산업공학회지
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    • 제22권2호
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    • pp.231-245
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    • 1996
  • Semiconductor manufacturing line includes several batch processes which are to be controlled effectively to enhance the productivity of the line. The key problem in batch processes is a dynamic batch sizing problem which determines number of lots processed simultaneously in a single botch. The batch sizing problem in semiconductor manufacturing has to consider delay of lots, setup cost of the process, machine utilization and so on. However, an optimal solution cannot be attainable due to dynamic arrival pattern of lots, and difficulties in forecasting future arrival times of lots of the process. This paper proposes an efficient batch sizing heuristic, which considers delay cost, setup cost, and effect of the forecast errors in determining the botch size dynamically. Extensive numerical experiments through simulation are carried out to investigate the effectiveness of the proposed heuristic in four key performance criteria: average delay, variance of delay, overage lot size and total cost. The results show that the proposed heuristic works effectively and efficiently.

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단일품목 동적 롯트량결정에 대한 이론적 고찰과 적용 (Single-prodect dynamic lot-sizing : review and extension)

  • 김형욱;김상천;현재호
    • 경영과학
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    • 제5권1호
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    • pp.56-70
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    • 1988
  • In this study, We reviewed the solution methods (for the heuristic and optimization method) for the single-item dynamic lot-sizing problem, and improved the efficiency (speed and optimality) of the conventional heuristic method by utilizing the inventory decomposition property. The iventory decomposition property decomposes the given original problem into several independent subproblems without violating the optimality conditions. Then we solve each decomposed subproblems by using the conventional heuristics such as LTC, LUC, Silver-Meal etc. For testing the efficiency of the proposed decomposition method, we adopted the data sets given in Kaimann, Berry and Silver-Meal. The computational results show that the suggested problem solving framework results in some promising effects on the computation time and the degree of optimality.

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