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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of the Korean Operations Research and Management Science Society
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Journal DOI :
The Korean Operations and Management Science Society
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Volume & Issues
Volume 27, Issue 4 - Dec 2002
Volume 27, Issue 3 - Sep 2002
Volume 27, Issue 2 - Jun 2002
Volume 27, Issue 1 - Mar 2002
Selecting the target year
A Comparison of the Discrimination of Business Failure Prediction Models
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 1~13
In this paper, we compares the business failure prediction accuracy among Linear Programming Discriminant Analysis(LPDA) model, Multivariate Discriminant Analysis (MDA) model and logit analysis model. The Data for 417 companies analyzed were gathered from KIS-FAS Published by Korea Information Service in 1999. The result of comparison for four time horizons shows that LPDA Is advantageous in prediction accuracy over the other two models when over all tilt ratio and business failure accuracy are considered simultaneously.
A Multi-Objective Decision Making Procedure for Web-based GDSS
Kim, Jae-Kyeong ; Cho, Yoon-Ho ;
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 15~31
This research suggests an interactive methodology for multiple objective linear programming problems to help the group select a compromising solution in the World Wide Web environment. Our methodology lessens the burden of group decision makers, which is one of necessary conditions of the web environment. Only the partial weak order of variables and objectives from the group decision makers are enough for searching the best compromising solution. For such a purpose, we expand the Dror and Gass algorithm to the group decision context. And we suggest the system architecture of a web-based GDSS for the Implementation of our methodology.
Machine Diagnosis and Maintenance Policy Generation Using Adaptive Decision Tree and Shortest Path Problem
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 33~49
CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.
Queues with Random Number of Vacations
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 51~61
By using the arrival time approach of Chae et at. , we derive various performance measures including the queue length distributions (in PGFs) and the waiting time distributions (in LST and PGF) for both M
/G/1 and Geo
/G/1 queueing systems, both under the assumption that the server, when it becomes idle, takes multiple vacations up to a random maximum number. This is an extension of both Choudhury and Zhang and Tian . A few mistakes in Zhang and Tian are corrected and meaningful interpretations are supplemented.
A Performance Evaluation Mode1 for Information Systems using the Balanced Scorecard and the Value Chain : A Case Study
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 63~79
During the last decade many enterprises spent a huge amount of money for investment on Information Technology (IT) & Information System (IS) to attain competitive advantage and to maximize their business performance by satisfying the various requirements of customers. Under such circumstances, methodologies for evaluating IT impact on business performance are very important issues for strategic decision making on investment. In this study, we propose a performance evaluation model that adopts the concept of the Balanced Scorecard (BSC) and the Value Chain to analyze the financial impact and non-financial impact of IT & IS at each critical work area. This model combines the 4 evaluation areas from BSC and 6 critical work areas from Value Chain and measures the Key Performance Indicator (HPI) and the effect of KPI. Also, we present a case study of which the evaluation model has been conducted on a major manufacturing company. finally. we address some important notes to improve the IT & IS performances in the real-world.
The Late Take-off Phenomenon in the Diffusion of Telecommunication Services : Focused on the Fax Markets
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 81~96
Telecommunication services are distinctive in that their adoptions are influenced by network effect resulting in 'the late take-off phenomenon' and the 'critical mass' problem. In this paper we examined, so called, 'the late take-off phenomenon' in the diffusion process of telecommunication services. We compared the parameters of the diffusion process of consumer durables with those of fax services in the US and Korea. By analyzing the parameters of a new diffusion model based on the threshold model proposed by Markus, we found that 'the late take-off phenomenon' resulted from the low heterogeneity of the threshold distribution for the potential adopters. A simulation approach was proposed for the theoretical implication of the 'critical mass' problem in the start-up telecommunications services.
A Genetic Algorithm for Dynamic Job Shop Scheduling
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 97~109
Manufacturing environments in the real world are subject to many sources of change and uncertainty, such as new job releases, job cancellations, a chance in the processing time or start time of some operation. Thus, the realistic scheduling method should Properly reflect these dynamic environment. Based on the release times of jobs, JSSP (Job Shoe Scheduling Problem) can be classified as static and dynamic scheduling problem. In this research, we mainly consider the dynamic JSSP with continually arriving jobs. The goal of this research is to develop an efficient scheduling method based on GA (Genetic Algorithm) to address dynamic JSSP. we designed scheduling method based on SGA (Sing1e Genetic Algorithm) and PGA (Parallel Genetic Algorithm) The scheduling method based on GA is extended to address dynamic JSSP. Then, This algorithms are tested for scheduling and rescheduling in dynamic JSSP. The results is compared with dispatching rule. In comparison to dispatching rule, the GA approach produces better scheduling performance.
An analysis of the
system with various vacations and set-up time
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 111~121
In this paper, we analyze an M
/G/1 with three types of vacation periods including setup time. Three types of vacations are : N-policy, single vacation, and multiple vacation. We consider compound poisson arrival process and general service time, where the server starts his service when a setup is completed. We find the PGF of the number of customers in system and LST of waiting time, with welch we obtain their means. A decomposition property for the system sloe and waiting time is described also.
Empirical Validation of Critical Success Factors on Organizational Performance in Korean Internet Venture
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 123~152
This study establishes key success Predictors of internet venture enterprises in Korea. The five factors are derived from the relevant literature and clarified the concept of entrepreneurship, industrial level, enterprise strategy, organizational capability, and resource procurement by distinguishing between its components and determinants. Organizational performance indicators were derived from the previous studies classifying by financial performance indicator and non-financial performance indicator using by recent evaluation method as BSC (Balanced Scorecard). We then examine the impact of critical success factors on the internet venture performance. Hypotheses on five factors of internet venture were tested for 103 organizations. Results indicate that critical success factors may serve as key predictors. Organizational strategy and resource capability was found to be positively influenced on both financial performance indicator and non-financial performance indicator while entrepreneurship, industrial level and organizational capability positively affected only non-financial performance indicator.
An Efficient Pricing Strategy(PAPANET) for Solving Network Flow Problems
Kang, Moonsig ;
Journal of the Korean Operations Research and Management Science Society, volume 27, issue 2, 2002, Pages 153~171
In this paper, we present an efficient pricing strategy, the pivot and probe Algorithm for Network Flow Problems(PAPANET), specifically for solving capacitated, linear network flow problem (NPs). The PAPANET begins with an initial relaxed network problem(RNP), consisting of all the nodes and initial candidate arcs(possibly a few least cost arcs form the original problem and a set of all the artificial and slack arcs). After an initial solution to the RNP is derived by pivoting, the PROBE procedure identifies a set of most violated arcs from the noncandidate arcs that are not considered to be in the current RNP, and adds them to the RNP. The procedure also discards a set of least favorable, zero flow, nonbasic arcs from the RNP. The new RNP is solved to optimality and the procedure continues until all of the dual constraints of the noncandidate arcs are satisfied by the dual solution to the RNP. The PAPANET effectively reduces the problem size, time per pivot, and solution CPU time by eliminating noncandidate arcs. Computational tests on randomly generated problems indicate that PAPANET achieves and average savings of 50-80% of the solution CPU time of that of a comparable standard network simplex implementation.