• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.39-47
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• 2006

In most of supply chain planning practices, the estimated demands, which are forecasted for each individual period in a forecasting window, are regarded as deterministic. But, in reality, the forecasted demands for the periods of a given horizon are stochastically distributed. Instead of using a safety stock, this study considers a direct control of service level by choosing the demand used in planning from the distributed forecasted demand values for the corresponding period. Using the demand quantile and echelon stock concept, we propose a simple but efficient heuristic algorithm for multi-echelon serial systems under service level constraints. Through a comprehensive simulation study, the proposed algorithm was shown to be very accurate compared with the optimal solutions.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• Journal of Mechanical Science and Technology
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• v.14 no.4
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• pp.380-392
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• 2000

A typical production-distribution system consist of three main echelons representing the retailer, distributors, and a factory each with an on-site warehouse. The system is sufficiently general and realistic to represent many industrial situations. However, decision functions and parameters have been selected to apply particularly to the production and distribution of consumer durables. The flows included in the model are materials, orders, and those information flows needed to support the material and order-rate decisions. In this work, a realistic production-distribution system has been used as a basic model, which consists of three sectors: retailer, distributor, and factory. That system is a nonlinear 25th-order continuous system interconnected between the echelons. Using a modern control algorithm, a typical multi-echelon production-distribution system using a dynamic controller is numerically simulated in the nominal plant and in the perturbed plant when the piecewise constant manufacturing decision is limited by a factory manufacturing upper-limit due to capital equipment, manpower, and factory lotsize.

• IE interfaces
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• v.19 no.2
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• pp.124-132
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• 2006

The system under study is a single item, multi-echelon distribution system with a capacitated production facility. All the nodes at the downstream ends are demand-sites, i.e., ordered items are delivered to the customers from the node. Also any transshipment depots in the midstream can be demand-sites as well. For a given planning period, at each of demand-site, demand is forecasted and known. Our objective is to minimize the average system cost per period which is the sum of holding and backorder costs in the entire network. Due to the capacity restrictions, it is difficult to establish efficient distribution planning. To overcome such a difficulty and obtain a reasonable and better solution, we convert this problem into a single machine earliness and weighted tardiness scheduling. We propose a simple but cost-effective heuristic for this problem. The experimental results showed that the proposed heuristic obtained much better solutions compared with another approach.

• Journal of Korean Society for Quality Management
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• v.36 no.2
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• pp.9-19
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• 2008

Spare part problem of MIME (Multi Indenture Multi Echelon) system under availability constraint has been studied for several decades. In most of existing studies, it was very difficult to obtain the optimal numbers of spare parts and some approximate methods were proposed under many restrictions. In this paper, we consider a simulation to estimate the total cost rate and system availability and a genetic algorithm to obtain the optimal numbers of spare parts. Some numerical examples are also studied.

• Journal of the Korean Society of Systems Engineering
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• v.12 no.2
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• pp.47-57
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• 2016

As the inventory costs of repairable items in military logistics continue to increase, many studies for optimal inventory level of these items are being carried out in advanced countries, including the US, to reduce these costs. Research on inventory level optimization for repairable items aimed to achieve the availability goal of a system with a MIME(Multi Indenture Multi Echelon) repair policy structure first began with Sherbrooke's METRIC and developed into various types. This research is to analyze and compare recent V-METRIC related studies to search for another variation in this field. This paper mainly looks at how to determine optimum inventory level for each repairable item to achieve a specific availability target within a limited budget, and also how to minimize inventory cost while achieving its availability target by determining optimal inventory level of each repairable item.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.61-68
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• 2019

Currently many companies are interested in reduction of the carbon emissions associated with their supply chain activities such as transportation and operations. Operational decisions, such as modifications in order quantities could an effective way in reducing carbon emissions in the supply chain. Cap-and-trade regulation, sometimes called emissions trading, is a market-based tool to limit greenhouse gas emissions. Under cap-and-trade regulation, emission credits are allocated to the firms and the firms trades emissions under cap-and-trade schemes. In this paper, we propose a single-manufacturer single-buyer two-echelon supply chain problem under the cap-and-trade mechanism incorporating the carbon emissions caused by transportation and warehousing activities where a single manufacturer produces a family of items in order to deliver a family of items to a single buyer at a fixed interval of time for effective implementation of Just-In-Time (JIT) Purchasing. An integrated multi-product lot-splitting model of facilitating multiple shipments in small lots between buyer and manufacturer is developed in a JIT Purchasing environment. Also, an iterative heuristic algorithm is developed to derive the common order interval, the number of intervals for each product and the number of shipments between the buyer and the manufacturer during the common interval. A numerical example is given to illustrate the savings in reduction of total cost and carbon emissions by the inventory model incorporating cap-and-trade mechanism compared to the classical inventory model. The proposed inventory model could be useful for the practical solution of two-echelon supply chain inventory problem under cap-and-trade mechanism.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.502-508
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• 2000

정보 시스템과 전자 상거래의 보편화로 실시간 판매 정보 공유가 용이하여짐에 따라, 공유 정보를 적절히 활용하는 재고 정책의 필요성이 증가하고 있다. 본 연구에서는 정보 공유 환경하의 one-warehouse multi-retailer 모델에서 개별 공유 정보를 보다 정확히 활용하여 재주문점 결정을 할 수 있는 방안을 제시하였다. 기존의 하위 계층의 재고량의 합에 기반하는 echelon stock policy 의 경우 상세 정보의 손실을 발생하는 문제가 있는 반면 본 연구에서는 개별 retailer 들의 재고량에 기반한 marginal savings의 개념을 정의하고, 이를 바탕으로 상세 정보에 기반한 재주문 정책을 제시하였다. 제시된 정책은 기존의 echelon stock policy 에 비해 우수한 결과를 나타냄을 실험을 통해 입증하였다.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.374-384
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• 2016

The efficiency of a supply chain can be extremely affected by its design which includes determining the flow pattern of material from suppliers to costumers, selecting the suppliers, and defining the opened facilities in network. In this paper, a multi-objective multi-echelon multi-product supply chain design model is proposed in which several suppliers, several manufacturers, several distribution centers as different stages of supply chain cooperate with each other to satisfy various costumers' demands. The multi-objectives of this model which considered simultaneously are 1-minimize the total cost of supply chain including production cost, transportation cost, shortage cost, and costs of opening a facility, 2-minimize the transportation time from suppliers to costumers, and 3-maximize the service level of the system by minimizing the maximum level of shortages. To configure this model a graph theoretic approach is used by considering channels among each two facilities as links and each facility as the nodes in this configuration. Based on complexity of the proposed model a multi-objective Pareto-based vibration damping optimization (VDO) algorithm is applied to solve the model and finally non-dominated sorting genetic algorithm (NSGA-II) is also applied to evaluate the performance of MOVDO. The results indicated the effectiveness of the proposed MOVDO to solve the model.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.37-44
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• 2001

Distribution System is considered as the most important part of SCM when the satisfaction of customer demand is considered. This paper focus on the backorder policies for stockout which is occurred in each regional distribution center of two-echelon distribution system facing stochastic demand process. Four concepts for the efficient system operation are suggested. First, at least 30% reduction of stockout is achieved by introduction of 50/25 allocation policy to distribution system. Second, transportation cost and lead-time of backorder are decreased by allowance of internal supply between regional distribution centers. Third, the frequency of emergency supply is minimized by application of Ship-up-to- expected-demand backorder policies. Finally we suggest several effective rules to select multi-internal suppliers. Simulation tests show the efficiency of our backorder policies and enhancement of customer service level.