• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.77-86
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• 2012

We consider the capacitated lot-sizing and scheduling problem for a paper remanufacturing system that produces several types of corrugated cardboards. The problem is to determine the lot sizes as well as the sequence of lots for the objective of minimizing the sum of setup and inventory holding costs while satisfying the demand and the machine capacity over a given planning horizon. In particular, the paper remanufacturing system has sequence-dependent setup costs that depend on the type of product just completed and on the product to be processed. Also, the setup state at one period can be carried over to the next period. An integer programming model is presented to describe the problem. Due to the complexity of the problem, we modify the existing two-stage heuristics in which an initial solution is obtained and then it is improved using a multi-pass interchange method. To show the performances of the heuristics, computational experiments were done using the real data, and a significant amount of improvement is reported.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.2
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• pp.169-175
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• 2021

The lot sizing problem(LSP) is a hard problem that classified as non-deterministic(NP)-complete because of the polynomial-time optimal solution algorithm is unknown yet. The well-known W-W algorithm can be obtain the solution within polynomial-time, but this algorithm is a very complex, therefore the heuristic approximated S-M algorithm is suggested. This paper suggests O(n) linear-time complexity algorithm that can be find not the approximated but optimal solution. This algorithm determines the lot size Xt∗ in period t to the sum of the demands of interval [t,t+k], the period t+k is determined by the holding cost will not exceed setup cost of t+k period. As a result of various experimental data, this algorithm finds the optimal solution about whole data.

• Journal of Korean Institute of Industrial Engineers
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• v.22 no.2
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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.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.802-810
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• 1998

The purpose of this study is to find the analytic solution of determining the optimal capacity of processes and storages to meet the product demand. Recent trend to reduce product delivery time and to provide high quality product to customer requires the increasing capacity of storage facilities. However, the cost of constructing and operating storage facilities is becoming substantial because of increasing land value, environmental and safety concern. Therefore, reasonable decision making about the capacity of processes and storages is important subject for industries. The industrial solution for this subject is to use the classical economic lot sizing method, EOQ(Economic Order Quantity) model, trimmed with practical experience but the unrealistic assumption of EOQ model is not suitable for the chemical plant design with highly interlinked processes and storages. This study, a first systematic attempt for this subject, clearly overcomes the limitation of classical lot sizing method. The superstructure of the plant consists of the network of serially and/or parallelly interlinked processes and storages. A novel production and inventory analysis method, PSW(Periodic Square Wave) model, is applied. The objective function of optimization is minimizing the total cost composed of setup and inventory holding cost. The advantage of PSW model comes from the fact that the model provide a set of simple analytic solution in spite of realistic description of material flow between process and storage. The resulting simple analytic solution can greatly enhance the proper and quick investment decision for the preliminary plant design confronting diverse economic situation.

• IE interfaces
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• v.9 no.2
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• pp.3-17
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• 1996

Productivity improvement is one of the most challenging problem facing the motor industry. This paper deals with the lot sizing and production scheduling problems of the side frame press shop in a domestic truck manufacturing company. The problems can not be solved simultaneously due to the computational complexity. Thus, we present a heuristic method which solves the two problems sequentially with the objective of maximizing the press utilization while maintaining a minimum inventory level. A micro-computer-based software is developed for easy implementation of the heuristic in the shop floor level.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.104-107
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• 2007

In this paper, we propose the coordination scheme in a single-manufacturer-multiple-retailer supply chain system. Traditionally, the bargaining power of the single manufacturer is superior to those of retailers. The business environment supported by the e-business scheme may give rise to new business behavior. The multitude of retailer requests the manufacturer to relax the his unilateral lot-sizing policy while they are willing to compensate more than the manufacturer's expected loss caused by abandon his superior bargaining power. The side payment aggregated by the multiple retailers is transferred to the manufacturer according to the degree of the manufacturer's relaxation from the current unilateral lot-sizing policy.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.7-11
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• 2007

This paper considers a shipment planning of products from manufacturers to a third-party warehouse for demands with production time windows where a demand must be replenished in its time window. The underling lot-sizing model also assumes cargo delivery cost in each inbound replenishment to the warehouse. For this model, an optimal O($nT^4$) is presented where n is the number of demands and T is the length of the planning horizon.

• Journal of Korean Institute of Industrial Engineers
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• v.10 no.1
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• pp.27-36
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• 1984

This paper examines the influence of the uncertainty in demand and lead time on the relative performances of ten well-known single stage lot-sizing rules in a rolling schedule environment. Two other factors, coefficient of variation and time between orders, which may affect the performances of the rules are also considered. To compare the rules under an identical condition, 100% service level is set by introducing safety stocks. The effects of various factor levels are checked statistically by the pairwise t-test and the results show that the uncertainty of the environment has a strong influence on the performance of the rules.

• Korean Management Science Review
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• v.5 no.1
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.29-39
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• 2009

In an environment of global competition, the success of a manufacturing corporation is directly related to how it plans and executes production in particular as well as to the optimization level of its process in general. This paper proposes a production planning algorithm for the Multi-Level, multi-item Capacitated Lot Sizing Problem (MLCLSP) in supply chain network considering back-order. MLCLSP corresponds to a mixed integer programming (MIP) problem and is NP-hard. Therefore, this paper proposes an effective algorithm, GRHS (GRASP-based Rolling Horizon Search) that solves this problem within reasonable computational time and evaluates its performance under a variety of problem scenarios.