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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 30, Issue 4 - Dec 2005
Volume 30, Issue 3 - Sep 2005
Volume 30, Issue 2 - Jun 2005
Volume 30, Issue 1 - Mar 2005
Selecting the target year
A New Algorithm for Designing WDM Mesh Networks
Lee Youngho ; Chang Yongwon ; Park Noik ; Lee Soonsuk ; Kim Youngbu ; Cho Kisung ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 1~15
In this paper, we deal with a mesh network design problem arising from the deployment of WDM for the optical internet. The mesh network consists of mesh topology for satisfying traffic demand while minimizing the cost of WDM, OXC, and fiber cables. The problem seeks to find an optimal routing of traffic demands in the network such that the total cost is minimized. We formulate the problem as a mixed-integer programming model and devise a tabu search heuristic procedure. Also we develop an optical internet design system that implements the proposed tabu search heuristic procedure. We demonstrate the computational efficacy of the proposed algorithm, compared with CPLEX 8.0.
An Effective Lateral Transshipment Policy to Improve the Service Level in the Supply Chain
Jeon Young Sang ; Lee Young Hae ; Jung Jung Woo ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 17~26
There is the uncertainty of demands at each retailer in the supply chain. To satisfy customers' demand, retailer must have enough inventory. Nevertheless, stockout is occurred for some retailers. A lateral transshipment policy can be effectively used to deal with stockout. The new lateral transshipment policy, referred to service level adjustment (SLA), is suggested. The difference between SLA and previous policies is the integration of an emergency lateral 'transshipment with a preventive lateral transshipment to efficiently respond customers' demand in the proposed policy. Additionally, the service level to decide the quantity of products is considered. Simulation experiment is executed to treat stochastic factors in the two-echelon supply chain. The proposed policy can reduce total cost and is more effective to the change of demand, penalty cost, and ordering cost than the currently used policies.
Scheduling for Parallel Machines with Family Setup Times
Kwon Ick-Hyun ; Shin Hyun-Joon ; Eom Dong-Hwan ; Kim Sung-Shick ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 27~41
This paper considers identical parallel machine scheduling problem. Each job has a processing time. due date. weight and family type. If a different type of job is followed by prior job. a family setup is incurred. A two phased heuristic is presented for minimizing the sum of weighted tardiness. In the first phase. using roiling horizon technique. group each job into same family and schedule each family. In the second phase. assign each job to machines using schedule obtained in the first phase. Extensive computational experiments and comparisons among other algorithms are carried out to show the efficiency of the proposed algorithm.
Mixed-product flexible assembly line balancing based on a genetic algorithm
Song Won Seop ; Kim Hyeong Su ; Kim Yeo Keun ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 43~54
A flexible assembly line (FAL) is a production system that assembles various parts in unidirectional flow line with many constraints and manufacturing flexibilities. In this research we deal with a FAL balancing problem with the objective of minimizing the maximum workload allocated to the stations. However, almost all the existing researches do not appropriately consider various constraints due to the problem complexity. Therefore, this study addresses a balancing problem of FAL with many constraints and manufacturing flexibilities, unlike the previous researches. We use a genetic algorithm (GA) to solve this problem. To apply GA to FAL. we suggest a genetic representation suitable for FAL balancing and devise evaluation method for individual's fitness and genetic operators specific to the problem, including efficient repair method for preserving solution feasibility. After we obtain a solution using the proposed GA. we use a heuristic method for reassigning some tasks of each product to one or more stations. This method can improve workload smoothness and raise work efficiency of each station. The proposed algorithm is compared and analyzed in terms of solution quality through computational experiments.
Support Vector Bankruptcy Prediction Model with Optimal Choice of RBF Kernel Parameter Values using Grid Search
Min Jae H. ; Lee Young-Chan ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 55~74
Bankruptcy prediction has drawn a lot of research interests in previous literature, and recent studies have shown that machine learning techniques achieved better performance than traditional statistical ones. This paper employs a relatively new machine learning technique, support vector machines (SVMs). to bankruptcy prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, we use grid search technique using 5-fold cross-validation to find out the optimal values of the parameters of kernel function of SVM. In addition, to evaluate the prediction accuracy of SVM. we compare its performance with multiple discriminant analysis (MDA), logistic regression analysis (Logit), and three-layer fully connected back-propagation neural networks (BPNs). The experiment results show that SVM outperforms the other methods.
Flexible Integration of Models and Solvers for Intuitive and User-Friendly Model-Solution in Decision Support Systems
Lee Keun-Woo ; Huh Soon-Young ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 75~94
Research in the decision sciences has continued to develop a variety of mathematical models as well as software tools supporting corporate decision-making. Yet. in spite of their potential usefulness, the models are little used in real-world decision making since the model solution processes are too complex for ordinary users to get accustomed. This paper proposes an intelligent and flexible model-solver integration framework that enables the user to solve decision problems using multiple models and solvers without having precise knowledge of the model-solution processes. Specifically, for intuitive model-solution, the framework enables a decision support system to suggest the compatible solvers of a model autonomously without direct user intervention and to solve the model by matching the model and solver parameters intelligently without any serious conflicts. Thus, the framework would improve the productivity of institutional model solving tasks by relieving the user from the burden of leaning model and solver semantics requiring considerable time and efforts.
Multiresponse Optimization Through A New Desirability Function Considering Process Parameter Fluctuation
Kwon Jun-Bum ; Lee Jong-Seok ; Lee Sang-Ho ; Jun Chi-Hyuck ; Kim Kwang-Jae ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 95~104
A desirability function approach to a multiresponse problem is proposed considering process parameter fluctuation which may amplify the variance of response. It is called POE (propagation of error), which is defined as the standard deviation of the transmitted variability in the response as a function of process parameters. In order to obtain more robust process parameter setting, a new desirability function is proposed by considering POE as well as distance-to-target of response and response variance. The proposed method is illustrated using a rubber product case in Ribeiro et al. (2000).
Brain Preference and Management : An Exploratory Reasoning from the Founders of Samsung and Hyundai Group, Lee and Chung
Lee Hong ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 105~128
The Purpose of the current study is to identify the differences between Samsung and Hyundai Group and the causes why the differences occurred. The study focuses on the founders of the two group as a main source of the differences, especially brain preference of the two founders. Two steps were employed to perform the study. Firstly, the two founders' characteristics were analyzed by using archival research. It was implicitly hypothesized that Group founders' characteristics explained the differences of the two Groups. It was found that the founder of Samsung Group, the late president Lee emphasized rationality, analysis, and cause/effect relationship and low risk taking, suggesting that he had left-brain preference. In contrast. the late president Chung, the founder of Hyundai Group, emphasized intuition, wholeness, contextual meaning, and risk taking, showing that he had right-brain preference. Secondly, a comparison between the two groups was performed in terms of business and financial risk in corporate portfolio, and management system. It was found that Hyundai Group was pursuing higher risk than Samsung Group. And it was observed that Samsung Group put more emphasis on formality in decision making and systematic control, and less emphasis on risk taking than Hyundai Group. From the two step research relationship between brian preference and management was reasoned. Research implications and limitations were discussed at the end of the study.
FAH-Based Expert Search Framework for Knowledge Management Systems
Yang Kun-Woo ; Huh Soon-Young ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 129~147
In Knowledge Management Systems (KMS), tacit knowledge which is usually possessed as forms like know-how, experiences, and etc. is hard to be systemized while managing explicit knowledge is comparatively easy using information technology such as databases, Recent researches in knowledge management have shown that it is more applicable in many ways to provide expert search mechanisms in KMS to pinpoint experts in the organizations with searched expertise so that users can contact them for help, In this paper, we propose an intelligent expert search framework to provide search capabilities for experts in similar or related fields according to the user's needs. In enabling intelligent expert searches, Fuzzy Abstraction Hierarchy (FAH) framework has been adopted, through' which finding experts with similar or related expertise is possible according to the subject field hierarchy defined in the system. To test applicability and practicality of the proposed framework, the prototype system, Knowledge Portal for Researchers in Science and Technology, was developed.
Application of (Max, +)-algebra to the Waiting Times in Deterministic 2-node Tandem Queues with Blocking
Seo Dong-Won ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 149~159
In this study, we consider characteristics of stationary waiting times in single-server 2-node tandem queues with a finite buffer, a Poisson arrival process and deterministic service times. The system has two buffers: one at the first node is infinite and the other one at the second node is finite. We show that the sojourn time or departure process does not depend on the capacity of the finite buffer and on the order of nodes (service times), which are the same as the previous results. Furthermore, the explicit expressions of waiting times at the first node are given as a function of the capacity of the finite buffer and we are able to disclose a relationship of waiting times between under communication blocking and under manufacturing blocking. Some numerical examples are also given.
Comparative Analysis of Multiattribute Decision Aids with Ordinal Preferences on Attribute Weights
Ahn Byeong Seok ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 161~176
In a situation that ordinal preferences on multiattribute weights are captured, we present two solution approaches: an exact approach and an approximate method. The former, an exact solution approach via interaction with a decision-maker, pursues the progressive reduction of a set of non-dominated alternatives by narrowing down the feasible attribute weights region. Subsequent interactive questions and responses, however, sometimes may not guarantee the best alternative or a complete rank order of a set of alternatives that the decision-maker desires to have. Approximate solution approaches, on the other hand, can be divided into three categories including surrogate weights methods, dominance value-based decision rules, and three classical decision rules. Their efficacies are evaluated in terms of choice accuracy via a simulation analysis. The simulation results indicate that a proposed hybrid approach, intended to combine an exact solution approach through interaction and a dominance value-based approach, is recommendable for aiding a decision making in a case that a final choice is seldom made at single step under attribute weights that are imprecisely specified beyond ordinal descriptions.
Algorithms for Determining the Geostationary Satellite Orbital Positions
Kim Soo-Hyun ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 177~185
We consider the optimization problem of the geostationary satellite orbital positions. which is very fundamental and important in setting up the new satellite launching plan. We convert the problem into a discrete optimization problem. However, the converted problem is too complex to find an optimal solution. Therefore, we develope the solution procedures using simulated annealing technique. The results of applying our method to some examples are reported.
Optimization Model on the World Wide Web Organization with respect to Content Centric Measures
Lee Wookey ; Kim Seung ; Kim Hando ; Kang Sukho ;
Journal of the Korean Operations Research and Management Science Society, volume 30, issue 1, 2005, Pages 187~198
The structure of a Web site can prevent the search robots or crawling agents from confusion in the midst of huge forest of the Web pages. We formalize the view on the World Wide Web and generalize it as a hierarchy of Web objects such as the Web as a set of Web sites, and a Web site as a directed graph with Web nodes and Web edges. Our approach results in the optimal hierarchical structure that can maximize the weight, tf-idf (term frequency and inverse document frequency), that is one of the most widely accepted content centric measures in the information retrieval community, so that the measure can be used to embody the semantics of search query. The experimental results represent that the optimization model is an effective alternative in the dynamically changing Web environment by replacing conventional heuristic approaches.