• Korean Management Science Review
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• v.21 no.2
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• pp.15-25
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• 2004

Great effort has been exerted to redesign the supply chain network as a means to improve corporate competitiveness. In this study, we present a mathematical model and a solution system to help redesign corporate logistics networks. The objective of the model is to minimize total logistics costs. We applied the solution system to real problem cases. We use the model and the concept to develop decision support system that is based on C++ with the use of CPLEX callable library as a solution engine. We tested and verified the DSS for redesigning the network of a large Korean electronics company. Through various scenario analyses. we recommend to redesign their supply chain network that demonstrates the possibility of substantial logistics cost savings.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.267-277
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• 1992

본 논문은 다목적선형계획법을 위한 Decision Support System ASEOV-VIM을 소개하고 있다. ASEOV-VIM에는 1) efficient solution set전체에 대한 개괄과 search direction을 제새하는 ASEOV; 2) decision maker의 preference information을 도출해내는 VIM; 3) 위 두 부분간의 interface로 활용되는 Mediator등 3개의 하부시스템이 있다. ASEOV-VIM은 TURBO-C를 이용하여 personal computer에 구현되었다.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.15
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• pp.6605-6608
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• 2015

Background: Colorectal cancer is a major cause of morbidity and mortality throughout the world. Colorectal cancer screening is an optimal way for reducing of morbidity and mortality and a clinical decision support system (CDSS) plays an important role in predicting success of screening processes. DSS is a computer-based information system that improves the delivery of preventive care services. The aim of this article was to detail engineering of information requirements and work flow design of CDSS for a colorectal cancer screening program. Materials and Methods: In the first stage a screening minimum data set was determined. Developed and developing countries were analyzed for identifying this data set. Then information deficiencies and gaps were determined by check list. The second stage was a qualitative survey with a semi-structured interview as the study tool. A total of 15 users and stakeholders' perspectives about workflow of CDSS were studied. Finally workflow of DSS of control program was designed by standard clinical practice guidelines and perspectives. Results: Screening minimum data set of national colorectal cancer screening program was defined in five sections, including colonoscopy data set, surgery, pathology, genetics and pedigree data set. Deficiencies and information gaps were analyzed. Then we designed a work process standard of screening. Finally workflow of DSS and entry stage were determined. Conclusions: A CDSS facilitates complex decision making for screening and has key roles in designing optimal interactions between colonoscopy, pathology and laboratory departments. Also workflow analysis is useful to identify data reconciliation strategies to address documentation gaps. Following recommendations of CDSS should improve quality of colorectal cancer screening.

• Korean Management Science Review
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• v.11 no.2
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• pp.161-184
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• 1994

The purpose of this paper is to suggest a DSS(Decision Support System) framework for managing exchange risks involved in international transactions. To this aim, a number of hedging strategies were suggested and analyzed in their pros and cons. Also, developed were a system architechture and various functional modules for implementing the suggested foreign exchange risk management system and application scenario was demonstrated. Finally, future research areas were indicated.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.747-749
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• 2003

For forest fire monitoring in relatively cool area like Siberia, design of Decision Support System (DSS) is proposed. The DSS is consisted of three different algorithms to detect potential fires from NOAA AVHRR image. The algorithm developed by CCRS (Canada Center for Remote Sensing) uses fixed thresholds for multi-channel information like one by ESA (European Space Agency). The algorithm of IGBP (International Geosphere Biosphere Program) involves contextual information in deriving fire pixels. CCRS and IGBP algorithms are rather liberal compared to more conservative ESA algorithm. Fire pixel information from the three algorithms is presented to the user. The user considers all these information in making decision about the location fire takes place.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.83-102
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• 2008

Ubiquitous computing requires timely supply of contextual information in order to upgrade decision quality. In this sense, this study is aimed at proposing a multi-dynamic decision support system for highly ill-structured problems. Especially, it is very important for decision makers in the ubiquitous computing to coordinate conflicts among local goals and global goal harmoniously. The proposed Multi-Dynamic Decision Support System (MDDSS) is basically composed of both central structure and distributed structure, in which central structure supports multi objects decision making and distributed structure supports individual decision making. Its hybrid architecture consists of decision processor, multi-agent controller and intelligent knowledge management processor. Decision processor provides decision support using contexts which come from individual agents. Multi-agent controller coordinates tension among multi agents to resolve conflicts among them. Meanwhile, intelligent knowledge management processor manages knowledge to support decision making such as rules, knowledge, cases and so on. To prove the validity of the proposed MDDSS, we applied it to an u-fulfillment problem system in which many kinds of decision makers exist trying to satisfy their own objectives, and timely adjustment of action strategy is required. Therefore, the u-fulfillment problem is a highly ill-structured problem. We proved its effectiveness with the aid of multi-agent simulation comprising 60 customers and 10 vehicles under three experimental modes.

• Asia pacific journal of information systems
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• v.8 no.3
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• pp.51-73
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• 1998

This paper is to evaluate the application potentials of data mining in the areas of Supply Chain Management (SCM) and to suggest the architectures of Decision Support Systems (DSS) that support data mining activities. We first briefly introduce data mining and review the recent literatures on SCM and then evaluate data mining applications to SCM in three aspects: marketing, operations management and information systems. By analyzing the cases about pricing models in distribution channels, demand forecasting and quality control, it is shown that artificial intelligence techniques such as artificial neural networks, case-based reasoning and expert systems, combined with traditional analysis models, effectively mine the useful knowledge from the large volume of SCM data. Agent-based information system is addressed as an important architecture that enables the pursuit of global optimization of SCM through communication and information sharing among supply chain constituents without loss of their characteristics and independence. We expect that the suggested architectures of intelligent DSS provide the basis in developing information systems for SCM to improve the quality of organizational decisions.

• Journal of Korea Water Resources Association
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• v.30 no.5
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• pp.431-439
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• 1997

This paper describes the development of a decision support system (DSS) for the real time reservoir operation that aims to maximize the flood control effect. In the decision support system, model base and real time data processing subsystem are included along with the graphical user interface(GUI) that is able to visualize the forecasted runoff hydrographs at the flood control points and reservoir water levels resulting from the model run as well as the current hydrologic status. The system was verified through the pseudo real time applications to the Taechong reservoir operation with the historical flood events of the Kum river basin occurred in July, 1987 and August, 1995, Decision making processes were performed using the developed system and the results were compared with the real operations at that time. The reservoir operation using the pseudo real time application of DSS were simulated by the flood runoff simulation model, that shows the reservoir operation by DSS were successful in flood control for the lower Kum River.

• Journal of Preventive Medicine and Public Health
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• v.23 no.1 s.29
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• pp.65-76
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• 1990

Hospitals are experiencing an increasing amount of financial difficulty due to government control of hospital rates since national health insurance has been implemented. The decision support system (DSS) was developed to provide cost and revenue information for the services rendered by each department in an effort to reduce costs. This information may be used to identify the causes of financial loss if cost exceeds revenue and to conduct variance analysis or portfolio analysis to improve financial situation of hospitals. The DSS was developed using a micro-mainframe interface approach where the mainframe computer collects and summarizes daily cost and revenue data and the micro computer computes the cost for each department. The significances of this paper are to determine the cost allocation basis and methods which are suitable to Korean situation and to apply DSS technology to the cost analysis.

• Journal of the Society of Naval Architects of Korea
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• v.46 no.3
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• pp.362-371
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• 2009

Shipbuilding is a typical 'build to order' industry. It has a business model that generates revenues from building various ships and offshore products in accordance with owner's requirements at each production stage. Under uncertainty in shipping market, it is very essential for the shipbuilder to prepare the fast and competitive decision for product portfolio strategy in order to maximize contribution margin by exploiting production facilities and constraints. In this study, we introduce the unique decision supporting methodology for the optimal product portfolio sets based on Theory of Constraints(TOC). This methodology is established by adopting the concept of Drum Buffer Rope(DBR) in constraints planning and Throughput Accounting (TA) in management accounting of TOC. In addition, Decision Supporting System(DSS) is implemented. This DSS system provides a throughput estimator with reflecting the cost structure of shipbuilding industry and a resource simulator built on heuristic algorithms to operate major constraint-resources in shipyard such as dock, quay and pre-erection area etc. Several examples are presented to show that the proposed methodology and system can effectively support the strategic decision-making process of a global shipbuilding company.