• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.113-127
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• 2006

We consider an integrated supply chain model in which multiple suppliers replenish items for a single buyer's demand. Also the buyer specifies a basic replenishment cycle and the suppliers replenish the items only at those time intervals. Namely, we propose a model to study and analyze the benefit by coordinating supply chain inventories through the basic replenishment cycle time. The objective of this model is to minimize the total relevant annual cost of the integrated inventory model. After developing proposed coordinated models, we suggest heuristics for searching the solutions of our models. Finally, numerical and computational experiments for each policy are carried out to evaluate the benefits of those models and the compensation policy is addressed to share the benefits.

• Industrial Engineering and Management Systems
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• v.12 no.3
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• pp.172-180
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• 2013

We herein consider a stochastic multi-item inventory management problem in which a warehouse sells multiple items with stochastic demand and periodic replenishment from a supplier. Inventory management requires the timing and amounts of orders to be determined. For inventory replenishment, trucks of finite capacity are available. Most inventory management models consider either a single item or assume that multiple items are ordered independently, and whether there is sufficient space in trucks. The order cost is commonly calculated based on the number of carriers and the usage fees of carriers. In this situation, we can reduce future shipments by supplementing items to an order, even if the item is not scheduled to be ordered. On the other hand, we can reduce the average number of items in storage by reducing the order volume and at the risk of running out of stock. The primary variables of interest in the present research are the average number of items in storage, the stock-out volume, and the number of carriers used. We formulate this problem as a multi-objective optimization problem. In a numerical experiment based on actual shipment data, we consider the item shipping characteristics and simulate the warehouse replenishing items coordinately. The results of the simulation indicate that applying a conventional ordering policy individually will not provide effective inventory management.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.661-664
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• 2006

Under a VMI (Vendor Managed Inventory) system, the vendor holds a certain level of control over not only inbound replenishment decisions on stocking but also outbound re-supply decisions. In this situation, vendor faces a better opportunity to synchronize the inventory and transportation decisions. However, shipment consolidation can reduce transportation expenses, but delivery time about the customer comes to be long and a customer service is fallen. Thus, a stock and transportation decision must consider this correlation. This study look into the relevant literature and suggest about further research direction.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.131-138
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• 2009

This paper considers a coordinated scheduling problem between multi-suppliers and an manufacture. When the supplier has insufficient inventory to meet the manufacture's order, the supplier may use the expedited production and the expedited transportation. In this case, we consider a scheduling problem to minimize the total cost of suppliers and manufacture. We suggest an population management genetic algorithm with local search and crossover (GALPC). By the computational experiments comparing with general genetic algorithm, the objective value of GALPC is reduced by 8% and the calculation time of GALPC is reduced by 70%.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.9-21
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• 2004

Semiconductor industry is the one whose supply chain network is distributed all over the world. And it has different characteristics with other manufacturing industries as reentrancy, binning, substitution. In this paper, we suggest supply chain models for the semiconductor industry, consisting of production and distribution chains, where manufacturing characteristics are considered. Three policies for the production chain and two policies for the distribution chain are suggested and formulated mathematically. Six combination policies are tested for the evaluation of performances with example. It is shown that the supply chain is operated, if production and distribution are coordinated and managed based on the demand information, without inventory, as efficiently as the chain with inventory.

• Korean Management Science Review
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• v.19 no.1
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• pp.107-116
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• 2002

A major challenge to supply chain managers is how to control inventories and costs along the supply chain while maximizing customer service Performance. In the literature, although the optimal management of inventory along the supply chain has received considerable attention during the past decades, the attention has been mainly given to multi-echelon control policies. A prerequisite for applying these policies is full information transparency in the supply chain, which is hard to accomplish in practice because it may require major organizational chanties. In the case that a decentralized control (local (R, S) policy) should be used at each location in multi-stave distribution systems, this paper presents the coordinating approach of determining the best policy which satisfies predetermined target customer service levels and minimizes the mean physical stock along the system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.157-158
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• 2021

Big data in the supply chain mainly comes from four aspects. One is the relevant data inevitably generated in the process of product value transfer of enterprises in the supply chain, such as production equipment quality data, planned procurement data, product data, etc; On the other hand, it is derived from the ERP data of various companies in the supply chain; The third is e-commerce data from the customer, and the last is data from external or manually entered data. A third-party data service center analysis and mining the data to predict and control the inventory in the process of supply chain operation. It brings innovation and change of management technology and way of thinking to the whole supply chain in many aspects, and finally achieves the goal of coordinated inventory and zero inventory of the whole supply chain.

• Management Science and Financial Engineering
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• v.11 no.1
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• pp.1-24
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• 2005

The results of a study of the coordination effect in stocking and promotional markdown policies for a supply chain consisting of a retailer and a discount outlet (DCO) are reported here. We assume that the product is sold in two consecutive periods: the Normal Sales Period (NSP) and the subsequent Promotional Markdown Sales Period (PSP). We first study an integrated supply chain in which managers in the two periods design a common system so as to jointly decide the stocking quantities, markdown time schedule, and markdown price to maximize mutual profit. Next, we consider a decentralized supply chain. An uncoordinated contract is designed in which decisions are decentralized to optimize the individual party's objective function. Here, three sources of system inefficiencies cause the decentralized system to earn a lower expected system profit than that in the integrated supply chain. The three sources are as follows: in the decentralized system the retailer tends to (1) stock less, and (2) keep a longer sales period, and the DCO tends to (3) stock fewer leftovers inventories and charge a higher markdown price. Finally, a numerical experiment is provided to compare the coordinated model with the uncoordinated model to explore factors that make coordination an effective approach.

• IE interfaces
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• v.13 no.3
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• pp.424-430
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• 2000

Supply chain management (SCM) is an area that has recently received a great deal of attention in the business community. While SCM is relatively new, the idea of coordinated planning is not. During the last decades, many researchers have investigated multi-stage inventory problems. However, only a few papers address the problem of cost-optimal coordination of multi-stage inventory control with respect to service measures. Even published approaches have a shortcoming in dealing with a delivery lead time consisted of a shipping time and a waiting time. Assumed that there is no waiting time, or that the delivery lead time is implicitly compounded of a shipping time and a waiting time, the problem is often simplified into a multi-stage buffer allocation and a single-stage stochastic buffer sizing problem at all installations. This paper presents a simulation-based heuristic algorithm and a comparison with others for the problem that cannot be decomposed into a multi-stage buffer allocation and a single-stage stochastic buffer sizing problem because the waiting time ties together all stages. The comparison shows that the simulation-based heuristic algorithm performs better than other approaches in saving average inventory cost for both Poisson and Normal demands.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.117-139
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• 2007

This paper contributes by incorporating works addressing supply chain coordination and investing in setup reduction program. Consider a two-echelon, EOQ-like inventory system consisting of a supplier and a buyer. We assume that both the supplier and the buyer can invest in setup cost reduction programs in order to benefit from small order sizes. However, the costs of investing in setup cost reduction programs are different for the two parties, leading to mismatches in individually optimal setup costs and order cycle times. We propose a supply chain coordination contract that makes use of quantity discount as an incentive transfer scheme for supply chain coordination.