Go to the main menu
Skip to content
Go to bottom
REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
> Journal Vol & Issue
Journal of Korean Institute of Industrial Engineers
Journal Basic Information
Journal DOI :
Korean Institute of Industrial Engineers
Editor in Chief :
Volume & Issues
Volume 27, Issue 4 - Dec 2001
Volume 27, Issue 3 - Sep 2001
Volume 27, Issue 2 - Jun 2001
Volume 27, Issue 1 - Mar 2001
Selecting the target year
An Algorithm for Optimal Inventory Level in Multi - Echelon Repairable - Item Inventory System with General Service Time distribution
Kim, Tai-Young ; Kim, Jong-Soo ; Hur, Sun ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 226~232
This paper presents an efficient method for the problem of determining the spare inventory level of a multi-echelon repairable-item inventory system. We consider the system with two levels of inventory, two levels of service and with a general service time distribution. We propose an algorithm that determines the spare inventory level to satisfy the minimum fill rate with the minimum cost. Experimental results show that the algorithm is accurate and efficient.
Development of the Forecasting Model for Parts in an Automobile
Hong, Jung-Sik ; Ahn, Jae-Kyung ; Hong, Suk-Kee ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 233~238
This paper deals with demand forecasting of parts in an automobile model which has been extinct. It is important to estimate how much inventory of each part in the extinct model should be stocked because production lines of some parts may be replaced by new ones although there is still demands for the model. Furthermore, in some countries, there is a strong regulation that the automobile manufacturing company should provide customers with auto parts for several years whenever they are requested. The major characteristic of automobile parts demand forecasting is that there exists a close correlation between the number of running cars and the demand of each part. In this sense, the total demand of each part in a year is determined by two factors, the total number of running cars in that year and the failure rate of the part. The total number of running cars in year k can be estimated sequentially by the amount of shipped cars and proportion of discarded cars in years 1, 2,
, i. However, it is very difficult to estimate the failure rate of each part because available inter-failure time data is not complete. The failure rate is, therefore, determined so as to minimize the mean squared error between the estimated demand and the observed demand of a part in years 1, 2,
, i. In this paper, data obtained from a Korean automobile manufacturing company are used to illustrate our model.
An Artificial Adaptation Model by Means of the Endoparasitic Evolution Process
Kim, Yeo-Keun ; Lee, Hyo-Young ; Kim, Jae-Yun ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 239~249
Competitive coevolution models, often called host-parasite models, are searching models that imitate the biological coevolution that is a series of reciprocal changes in two competing species. The models are known to be an effective method of solving complex and dynamic problems such as game problems, neural network design problems and constraint satisfaction problems. However, previous models consider only ectoparasites that live on the outside of the host when designing the models, not considering endoparasites that live on the inside of the host. This has a limitation to exploiting some information. In this paper, we develop an artificial adaptation model simulating the process in which hosts coevolve with both ectoparasites and endoparasites. In the model, the endoparasites play important roles as follows. By means of them, we can keep the history on results of previous competition between hosts and parasites, and use endogeneous fitness, not exogeneous. Extensive experiments are carried out to show the coevolution phenomenon and to verify the performance of the proposed model. Nim game problems and neural network problems are used as test-bed problems. The results are reported in this paper.
A Study for a Capacitated Facility Location Problem on a Tree Structured Network
Cho, Geon ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 250~259
Given a tree structured network in which each node has its own demand and also stands for a candidate location of a potential facility, such as plant or warehouse, a capacitated facility location problem on the network (CFLPOT) is to decide capacitated facility locations so that the total demand occurred on the network can be satisfied from those facilities with the minimum cost. In this paper, we first introduce a mixed integer programming formulation for CFLPOT with two additional assumptions, the indivisible demand assumption and the contiguity assumption and then show that it can be reformulated as a tree partitioning problem with an exponential number of variables. We then show that it can be solved in O(
) time by utilizing the limited column generation method developed by Shaw (1993), where n is the total number of nodes in the network and b is the maximum facility capacity. We also develop a depth-first dynamic programming algorithm with a running time of O(nb) for finding the locally maximal reduced cost which plays an important role in the limited column generation method. Finally, we implement our algorithms on a set of randomly generated problems and report the computational results.
Properties and Approximation Method of the Random - Request Availability
Lee, Kang-W. ; Park, Jung-W. ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 260~266
The characteristic of the random-request availability is that random task arrival is included as one of system elements. If the mean number of task arrivals grows, the computational complexity for deriving the random-request availability becomes extremely high. Using a simulation method, the effect of 'random task arrival' elements on the random-request availability is investigated. Some approximation methods are also discussed.
A Choice-Based Competitive Diffusion Model with Applications to Mobile Telecommunication Service Market in Korea
Jun, Duk-Bin ; Kim, Seon-Kyoung ; Cha, Kyung-Cheon ; Park, Yoon-Seo ; Park, Myoung-Hwan ; Park, Young-Sun ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 267~273
While forecasting sales of a new product is very difficult, it is critical to market success. This is especially true when other products have a highly negative influence on the product because of competition effect. In this paper, we develop a choice-based competitive diffusion model and apply to the case where two digital mobile telecommunication services, that is, digital cellular and PCS services, compete. The basic premise is that demand patterns result from choice behavior, where customers choose a product to maximize their utility. In comparison with Bass-type competitive diffusion models, our model provides superior fitting and forecasting performance. The choice-based model is useful in that it enables the description of such competitive environments and provides the flexibility to include marketing mix variables such as price and advertising.
Interior Point Methods for Multicommodity Flow Problems
Lim, Sung-Mook ; Seol, Tong-Ryeol ; Park, Soon-Dal ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 274~280
In this research, we develop a specialized primal-dual interior point solver for the multicommodity flow problems (MCFP). The Castro's approach that exploits the problem structure is investigated and several aspects that must be considered in the implementation are addressed. First, we show how preprocessing techniques for linear programming(LP) are adjusted for MCFP. Secondly, we develop a procedure that extracts a network structure from the general LP formulated MCFP. Finally, we consider how the special structure of the mutual capacity constraints is exploited. Results of comupational comparison between our solver and a general interior point solver are also included.
Generalized Clustering Algorithm for Part-Machine Grouping with Alternative Process Plans
Kim, Chang-Ouk ; Park, Yun-Sun ; Jun, Jin ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 281~288
We consider in this article a multi-objective part-machine grouping problem in which parts have alternative process plans and expected annual demand of each part is known. This problem is characterized as optimally determining part sets and corresponding machine cells such that total sum of distance (or dissimilarity) between parts and total sum of load differences between machines are simultaneously minimized. Two heuristic algorithms are proposed, and examples are given to compare the performance of the algorithms.
Multivariate Control Chart for Autocorrelated Process
Nam, Gook-Hyun ; Chang, Young-Soon ; Bai, Do-Sun ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 289~296
This paper proposes multivariate control chart for autocorrelated data which are common in chemical and process industries and lead to increase in the number of false alarms when conventional control charts are applied. The effect of autocorrelated data is modeled as a vector autoregressive process, and canonical analysis is used to reduce the dimensionality of the data set and find the canonical variables that explain as much of the data variation as possible. Charting statistics are constructed based on the residual vectors from the canonical variables which are uncorrelated over time, and therefore the control charts for these statistics can attenuate the autocorrelation in the process data. The charting procedures are illustrated with a numerical example and Monte Carlo simulation is conducted to investigate the performances of the proposed control charts.
Cost of Ownership Model for the Inspection Equipment of Multiple Quality Attributes
Sohn, So-Young ; Moon, Hyoung-Uk ; Hong, Cheol-Kee ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 297~304
Procurement decisions for inspection equipment are often made heavily based on the initial purchase price instead of the effects of inspection cost, equipment calibration and utilization over the lifetime. Cost of ownership(COO) models that take into account all of these cost factors together have been developed focusing on a single quality characteristic. In modern manufacturing environment, inspection equipment often can deal with more than one quality characteristic simultaneously. In this paper, we propose the revised COO model for the economic evaluation of the inspection equipment that can accommodate multiple quality characteristics. We also employ an engineering economy model to compare equipments with different life span. Software is developed for handy comparison of the COO of alternative equipments along with sensitivity analysis far the optimal procurement decision.
Evaluation System of Psychological Feelings for Corporate Identity Symbol Marks Using Fuzzy Neural Networks
Chang, In-Seong ; Park, Yong-Ju ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 305~314
In this paper, we construct an automatic evaluation system of psychological feeling for corporate identity (CI) symbol mark based on a fuzzy neural network technique. The system is modelled by trainable fuzzy inference rules with several input variables (qualitative and quantitative design components of CI symbol mark) and a single output variable (consumer's feeling). The back propagation learning algorithm, which is a conventional learning method of multilayer feedforward neural networks, is used for parameter identification of the fuzzy inference system. The learning ability to train data and the generalization ability to test data are evaluated for the proposed evaluation system by computer simulations.
Simulated Annealing Algorithms for Operation Sequencing in Nonlinear Process Planning
Lee, Dong-Ho ; Dimitris, Kiritsis ; Paul, Xirouchakis ;
Journal of Korean Institute of Industrial Engineers, volume 27, issue 3, 2001, Pages 315~327
This paper considers the problem of operation sequencing in nonlinear process planning, which is the problem of selecting and sequencing operations required to produce a part with the objective of minimizing the sum of operation processing costs and machine, setup and tool change costs. Main constraints are the precedence relations among operations. The problem can be decomposed into two subproblems: operation selection and operation sequencing. We suggest four simulated annealing algorithms, which solve the two subproblems iteratively until a good solution is obtained. Here, the operation selection problem can be solved using a shortest path algorithm. Application of the algorithms is illustrated using an example. Also, to show the performances of the suggested algorithms, computational experiments were done on randomly generated test problems and the results are reported. In particular, one of the suggested algorithms outperforms an existing simulated annealing algorithm.