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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 18, Issue 3 - Dec 1993
Volume 18, Issue 2 - Aug 1993
Volume 18, Issue 1 - Apr 1993
Selecting the target year
Mixed Model Assembly Line Balancing with the Related Task Consideration
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 1~22
This paper deals with the problem of mixed model assembly line balancing. In mixed model assembly lines, tsks should be assigned to stations in such a manner that all stations have approximately the same amount of work on a production cycle basis. Further in balancing assembly lines, the related tasks, the performing task side and the team tasks should be considered to improve work methods, to give more job satisfaction to workers, and to allow greater flexibility in the design of assembly lines. In this paper, the heuristic dispatch assignment rule is developed to assign evenly tasks of each model to all stations. The heuristic method based on the assignment rule developed is presented for mixed model assembly line balancing with the considerations of the related tasks, the performing task side, and the team tasks. The proposed method is analyzed, and compared with other methods for line balancing.
A Study on the Development of Progress Control Algorithm Using the Fuzzy K-longest Path Algorithm
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 23~43
This paper employs fuzzy variables instead of deterministic variables for job times in a project network. A fuzzy variable has its value restricted by a possibility distribution. This paper utilizes the triangular possibility distribution which has three estimated times. That is normal, resonable, and crash job times. This paper develops a fuzzy k-longest path algorithm, by utilizing the k-longest path algorithm. This algorithm will be useful to control the project the project network by considering the project completion possibility.
Multiattribute Stochastic Statistical Dominance in Decision Making with Incomplete Information
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 45~55
In multiattribute decision making a decision maker (DM) can choose the best alternative if his/her multiattribute utility function and the joint probability distribution of outcomes are exactly known. This paper develops multiattribute stochastic-statistical dominance rules which can be applied to the situation when neither of them is known exactly, that is, when the DM cannot calculate the expected utility for each alternative. First, the notion of relative risk aversion is used dominance rules are developed to screen out dominated alternatives so that hi/she choose the best one among the remaining nondominated alternatives.
A Comparative Study on the Bankruptcy Prediction Power of Statistical Model and AI Models: MDA, Inductive,Neural Network
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 57~81
This paper is concerned with analyzing the bankruptcy prediction power of three methods : Multivariate Discriminant Analysis (MDA), Inductive Learning, Neural Network, MDA has been famous for its effectiveness for predicting bankrupcy in accounting fields. However, it requires rigorous statistical assumptions, so that violating one of the assumptions may result in biased outputs. In this respect, we alternatively propose the use of two AI models for bankrupcy prediction-inductive learning and neural network. To compare the performance of those two AI models with that of MDA, we have performed massive experiments with a number of Korean bankrupt-cases. Experimental results show that AI models proposed in this study can yield more robust and generalizing bankrupcy prediction than the conventional MDA can do.
A Simulated Annealing Method for the Optimization Problem in a Multi-Server and Multi-Class Customer Ssystem
Yoo, Seuck-Cheun ;
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 83~103
This paper addresses an optimization problem faced by a multi-server and multi-class customer system in manufacturing facilities and service industries. This paper presents a model of an integrated problem of server allocation and customer type partitioning. We approximate the problem through two types of models to make it tractable. As soution approach, the simulated annealing heuristic is constructed based on the general simulated annealing method. Computational results are presented.
A Model for Material Handling is an Elevator System
Kim, Seung-Nam ;
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 105~130
This study deals with finding a schedule for the movement of a material handling device (elevator) in a manufacturing plant. Two different algorithm (Traveling Salesman Technique and Greedy Algorithm) are used in the scheduling of the elevators using a simulation technique to determine the proper method of scheduling the elevator movement. Based on the simulation analysis, we have found that the Greedy algorithm serves better than the algorithm based on Traveling Salesman technique for scheduling the movement of a material handling device in the manufacturing plant.
An Approach to Double Hoist Scheduling in the Chemical Processes
Lim, Joon-Mook ; Hwang, Hark ;
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 131~145
This paper deals with scheduling problem of the chemical process system where aircraft parts go through a given sequence of tanks filled with chemical solutions. The system has two hoists which move carriers holding the parts between tanks. A mixed integer programming model is developed from which a maximum throughput schedule can be found for the hoist movements. To show the validity of the model, a real world problem is solved and the results are compared with those with an existing approach.
A Dual Problem and Duality Theorems for Average Shadow Prices in Mathematical Programming
Cho, Seong-Cheol ;
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 147~156
Recently a new concept of shadow prices, called average shadow price, has been developed. This paper provides a dual problem and the corresponding duality theorems justifying this new shadow price. The general duality framework is used. As an important secondary result, a new reduced class of price function, the pp. h.-class, has been developed for the general duality theory. This should be distinguished from other known reductions achieved in some specific areas of mathematical programming, in that it sustains the strong duality property in all the mathematical programs. The new general dual problem suggested with this pp. h.-class provides, as an optimal solution, the average shadow prices.
The Impact of Reliability Growth on Spares Provisioning
Jung, Won ;
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 157~173
Reliability growth modeling can be a requirement when bidding on large military hardware systems. Under current reliability warranty legislature, the reliability growth model can be later translated into necessary reliability performance which must be demonstrated over an extended period of usage. In this paper the modeling situation is concerned with determining the number of spares needed to support a projected reliability growth both at the fightine and in a depot inventory. The model differs from existing models for logistics planning in that we allow for the phenomena of reliability growth. The model can also be used to determine central depot staffing requirements based upon a specified system utilization.
A Probabilistic Order Level System When Delay in Payment Is Permissible
Shah, Mita H. ;
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 175~182
The probabilistic order level inventory model is developed when a supplier allows some credit period T for settling the accounts for purchase quantity. The credit period T is known constant. Mathematical models are derived for both the cases i) T'.leq. T and ii) T'>T. Expressions are derived for average expected total cost of the system, the optimum cycle time and for obtaining optimum order level S = S
in each case. The exmaples are given to illustrate the model.
Splitting Algorithm Using Total Information Gain for a Market Segmentation Problem
Kim, Jae-Kyeong ; Kim, Chang-Kwon ; Kim, Soung-Hie ;
Journal of the Korean Operations Research and Management Science Society, volume 18, issue 2, 1993, Pages 183~203
One of the most difficult and time-consuming stages in the development of the knowledge-based system is a knowledge acquisition. A splitting algorithm is developed to infer a rule-tree which can be converted to a rule-typed knowledge. A market segmentation may be performed in order to establish market strategy suitable to each market segment. As the sales data of a product market is probabilistic and noisy, it becomes necessary to prune the rule-tree-at an acceptable level while generating a rule-tree. A splitting algorithm is developed using the pruning measure based on a total amount of information gain and the measure of existing algorithms. A user can easily adjust the size of the resulting rule-tree according to his(her) preferences and problem domains. The algorithm is applied to a market segmentation problem of a medium-large computer market. The algorithm is illustrated step by step with a sales data of a computer market and is analyzed.