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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 23, Issue 4 - Dec 1998
Volume 23, Issue 3 - Sep 1998
Volume 23, Issue 2 - Jun 1998
Volume 23, Issue 1 - Mar 1998
Selecting the target year
Zone Clustering Using a Genetic Algorithm and K-Means
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 1~16
The zone clustering problem arising from several area such as deciding the optimal location of ambient measuring stations is to devide the 2-dimensional area into several sub areas in which included individual zone shows simimlar properties. In general, the optimal solution of this problem is very hard to obtain. Therefore, instead of finding an optimal solution, the generation of near optimal solution within the limited time is more meaningful. In this study, the combination of a genetic algorithm and the modified k-means method is used to obtain the near optimal solution. To exploit the genetic algorithm effectively, a representation of chromsomes and appropriate genetic operators are proposed. The k-means method which is originally devised to solve the object clustering problem is modified to improve the solutions obtained from the genetic algorithm. The experiment shows that the proposed method generates the near optimal solution efficiently.
Design of Cellular Manufacturing Systems Integrating Automated Guided Vehicles under a Tandem Configuration
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 17~28
This study suggests a procedure for designing cellular manufacturing systems (CMS) which are combined with automated guided vehicles (AGVs) using a tandem configuration. So far most of the previous studies have dealt with conventional design problems not considering the layout and the characteristics of transporters used in CMS. A mathematical model is developed using the service time to perform material transfers as a suitable meassure. The service capacity of AGVs and space limitations are also reflected in this model. As the model can be shown strongly NP-hard, a heuristic algorithm is presented, in which each cell is temporarily formed using both the set covering model and similarity coefficients, and then locations of the cells are determined by means of tabu search and finally machine perturbations are carried out. An example problem is solved to demonstrate the algorithm developed.
Single Machine Dcheduling with Maximum Allowable Tardiness in ET Model
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 29~41
This paper addresses the problem of scheduling a set of jobs with a common due data on a single machine. The objective is to minimize the sum of the earliness and tardiness of jobs subject to
. Properties for the
problem are found and the problem is shown to be NP-complete in the ordinary sense. According to the range of Δ, the problem can be solved in polynomial time. Also, some special cases where an optimal schedule is found in polynomial time are discussed.
Stochastic (Q, r) Inventory Model for Two-echelon Distrubution System
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 43~65
This paper develops a two-echelon inventory model with time-weighted partial backorders. The presented model assumed to follow continuous review (Q. r) policy for both the retailers and the central warehouse under stochastic demand. A heuristic method to find an optimum-tending solution for total variable system cost per year incurred at the central warehouse and retailers in a system is suggested. To show the usefulness of the above model, numericla examples are illustrated for verification and validation purpose.
Developing Job Flow Time Prediction Models in the Dynamic Unbalanced Job Shop
Kim, Shin-Kon ;
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 67~95
This research addresses flow time prediction in the dynamic unbalanced job shop scheduling environment. The specific purpose of the research is to develop the job flow time prediction model in the dynamic unbalance djob shop. Such factors as job characteristics, job shop status, characteristics of the shop workload, shop dispatching rules, shop structure, etc, are considered in the prediction model. The regression prediction approach is analyzed within a dynamic, make-to-order job shop simulation model. Mean Absolute Lateness (MAL) and Mean Relative Error (MRE) are used to compare and evaluate alternative regression models devloped in this research.
Optimal Redundant Units and Load in Parallel Systems
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 97~107
This paper is concerned with a parallel system that sustains a time-independent load and consists of n components with exponential lifetimes. It is assumed that the total load is shared by the working components and the failures of components increase higher failure rates in the surviving components according to the relationship between the load and the fialure rates. The power rule model among several load-failure rate relationships is considered. We consider the system efficiency meausre as the expected profit earned by the system per unit time. The high load causes high gain but it also occurs frequent system failures. The expected profit per unit time is used as criterion to evaluate the system efficiency. The goal of system engineer is to determine the optimal load and redundant units maximizing the expected profit per unit time. First, the system reliability function is obtained and the optimization problem of the load-sharing parallel system is considered. Given the redundant units, the existence of the optimal load can be proved analytically and given the load, the optimal redundant units can be solved also analytically. The optimal load and redundant units are obtained simultaneously by numerical computation. Some numerical examples are studied.
Robustness of Data Mining Tools under Varting Levels of Noise:Case Study in Predicting a Chaotic Process
Kim, Steven H. ; Lee, Churl-Min ; Oh, Heung-Sik ;
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 109~141
Many processes in the industrial realm exhibit sstochastic and nonlinear behavior. Consequently, an intelligent system must be able to nonlinear production processes as well as probabilistic phenomena. In order for a knowledge based system to control a manufacturing processes as well as probabilistic phenomena. In order for a knowledge based system to control manufacturing process, an important capability is that of prediction : forecasting the future trajectory of a process as well as the consequences of the control action. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes, includinb chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a chaotic process in the presence of various patterns of noise.
An Improved Method of Method of Fuzzy Approximate Reasoning by Combining Self-Organizing Feature Map and Fuzzy Logic
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 143~159
This paper proposes a new type of fuzzy approximate reasoning method that combines a self organizing feature map and a fuzzy logic. Previous methods considered only input part to determine the number of fuzzy rules, while this paper considers both input and output parts simultaneously. Our approach proved to improve the inference performance. We also developed a new index for avoiding overlearning which guarantees more accurate results. Experimental results showed that our approach surpasses the performance of Takagi & Hayashi (1991) approach.
A Psychometric Method for Structuring Expert Knowledge:Application to Developing Credit Analysis Espert System for Small-Medium Companies Using Nonfinancial Statement Information
Journal of the Korean Operations Research and Management Science Society, volume 23, issue 1, 1998, Pages 161~181
Translating expert knowledge into production rules has been the most difficult and time-consuming when building expert systems (Buchanan et al. 1983). Especially, buidling hierarchical structure, i. e. developing sequential or dominant relationship among production rules is one of the most important and difficult processes. Hierarchical relationship among rules has been typically determined in the course of interviewing human experts. Since this interviewing procedure is rather subjective, however, the hierarchically structured rules produced in terms of interviewing is widely exposed to the severe discussion about their validity (Nisbett and Wilson 1977 : Ericsson and Simon 1980 : Kellog 1982). We thus need an objective method to effectively translate human expert knowledge into structured rules. As such a method, this paper suggests the order anlaysis technique that has been studied in psychometries (Cliff 1977 : Reynolds 1981 : Wise 1983). In this paper we briefly introduce the order analysis and explain how it can be applied to building hierarchical structure of production rules. We also illustrate how bankrupcy prediction rules of small-medium companies can be developed using this order analysis technique. Further, we validata the effectiveness of these rules developed by the order analysis, in comparison with those built by other methods. The rules developed by the proposed outperform those of the other traditional methods in effectively screening the bankrupted firms.