• Industrial Engineering and Management Systems
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• v.9 no.3
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• pp.227-241
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• 2010

A memory module industry's supply chain usually consists of multiple manufacturing sites and multiple distribution centers. In order to fulfill the variety of demands from downstream customers, production planners need not only to decide the order allocation among multiple manufacturing sites but also to consider memory module industrial characteristics and supply chain constraints, such as multiple material substitution relationships, capacity, and transportation lead time, fluctuation of component purchasing prices and available supply quantities of critical materials (e.g., DRAM, chip), based on human experience. In this research, a directed graph-based supply network planning (DGSNP) model is developed for memory module industry. In addition to multi-site order allocation, the DGSNP model explicitly considers production planning for each manufacturing site, and purchasing planning from each supplier. First, the research formulates the supply network's structure and constraints in a directed-graph form. Then, a proposed genetic algorithm (GA) solves the matrix form which is transformed from the directed-graph model. Finally, the final matrix, with a calculated maximum profit, can be transformed back to a directed-graph based supply network plan as a reference for planners. The results of the illustrative experiments show that the DGSNP model, compared to current memory module industry practices, determines a convincing supply network planning solution, as measured by total profit.

• IE interfaces
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• v.17 no.4
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• pp.472-481
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• 2004

In this paper, we propose a linear programming model of supply planning process for the supply chain collaboration strategy of a company. The amount of its supplying quantity relies on outsourcing suppliers heavily. Conversely, the revenues of those suppliers are highly dependent on the supplying quota from the supply network planning of the company. In order to keep the supply stable through collaboration, the company builds such a policy to guarantee the fairness on revenue between the supplies. For this, the supply network plan should keep the capacity utilization ratio even for all the suppliers. But the production capacities are different and the distribution of molds is disproportional through suppliers, so the supply network plan is not easily established with simple arithmetic processes. Therefore, we developed the linear programming model with those target function and constraints minimizing the costs for holding inventory and penalty of delayed delivery, simultaneously guaranteeing the even capacity utilization through suppliers. The proposed model has been applied to real case and the evaluation for the planning result from the model would be followed in order to make sure that our model guarantee on extracting the supply network plan subordinated to the policy. Also we mention about further studies for improvement of the model.

• Korean Management Science Review
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• v.30 no.1
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• pp.25-41
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• 2013

This paper presents a supply chain framework with the ODM (Original Design Manufacturing)-OEM (Original Equipment Manufacturing) hybrid production of textile industry in FTA (Free Trade Agreements) environments between Korea and other countries. The proposed supply chain framework with ODM-OEM hybrid production is a unique supply chain that has both domestic production with non-tariff advantages in FTA environment and oversea production with low labor costs. To investigate the validity of the proposed supply chain, we first construct its strategic profit model and supply chain planning and then show that each member of supply chain network-yarn manufacturer, fabric manufacturer, and apparel manufacturer-can maximize their own profits without conflicts among the members. The efficiency of the ODM-OEM hybrid production system is analytically verified in comparison with the general OEM and ODM production model using profit models. Comprehensive numerical examples are provided to illustrate the advantages of the proposed system.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.65-74
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• 2020

Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.269-272
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• 2001

In this paper, we presents a systematic methodology for minimizing tardiness and maximizing resource utilization in a multi-plant supply chain. A methodology is represented to a multi-objective mathematical program model. The model offers flexible and efficient multi-plant planning and scheduling. Also, We develope a realistic and flexible planning model using the genetic algorithm to solve the model.

• IE interfaces
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• v.15 no.1
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• pp.40-48
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• 2002

Recently, in the competitive environments, every company recognizes the importance of supply network planning models. However, there are so many problems in correctly applying mathematical model to the real world. Because mathematical modeling packages charge planning managers with understanding the models and responsibility for generating plans, fast and accurate model cannot be generated with ease. In this paper, we design the model management system that helps planning managers flexibly create and modify mathematical models and manage model versions. We implement the system with model base concept.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.143-156
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• 2005

Facility location planning (FLP) problem is the strategic level planning in supply chain. The FLP is significantly affected by the operation time of each facility. In most of the FLP researches, operation time of facility has been treated as a fixed value. However, the operation time is not a static factor in real situations and the fixed operation time may lead unrealistic FLP. In this paper, a mixed integer programming (MIP) model is proposed for solving the 3-stage FLP problem and operation times are adjusted by the results from the simulation model and an iterative approach combining the analytic model and simulation model is proposed to obtain more realistic operation plans for FLP problems.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.2
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• pp.77-93
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• 1995

A mathematical model for long-rage water supply planning was formulated as a dynamic plant location problem with network arc capacity expansion, and illustative example was presented. The proposed solution procedure identifies economical construction timings of surface water supply facilities and water conveyence systems and the best water supply operating patterns as well. In this study, we present a heuristic solution procedure using Simulated annealing Method in conjunction with Bertsekas & Tseng's RELAXT-II for the 0-1 integer network problem.

• Journal of Information Technology Applications and Management
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• v.15 no.1
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• pp.83-97
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• 2008

Today's competitive global market makes most enterprise endeavor to specialize their business areas, and co-operate with trading partners in supply chain by the forms of collaboration, information and business process sharing. However, even the supply chain plan generated by co-operation often fails to be executed successfully, because it was generated without capacities of suppliers and more over nested suppliers. To overcome this limitation, the supply chain plan of an enterprise should be generated truly integrated way. In this paper, we classify business patterns based on scenarios about quotation processing and supply chain planning in self-integrated environment. And we present business process models about four business patterns and describe them, which are classified by whether request for quotation includes information about price, required time periods, and quantity for each required time period and whether it is received from customer or sent to supplier. In addition, we describe the types of supply chain planning problem.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.51-58
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• 1990

A deterministic capacity expansion planning model for a two-capacity type facility is analyzed to determine the sizes to be expanded in each period so as to supply the known demands for two distinct capacity type(product) on time and to minimize the total cost incurred over a finite planning horizon of T periods. The model assumes that capacity unit of the facility simultaneously serves a prespecified number of demand units of each capacity type, that capacity type 1 can be used to supply demands for capacity type 2, but that capacity type 2 can't be used to supply demands for capacity type 1. Capacity expansion and excess capacity holding cost functions considered are nondecreasing and concave. The structure of an optimal solution is characterized and then used in developing an efficient dynamic programming algorithm that finds optimal capacity planning policy.