• Industrial Engineering and Management Systems
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• v.9 no.2
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• pp.121-130
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• 2010

In today's uncertain economic environment, economic risk is inherent in making large investments on manufacturing facilities. It is, therefore, practically meaningful to divide investment over multiple periods, reducing the risk of investment. Then, the cash-flow over the entire planning horizon would comprise positive inflow and negative outflow. In this case, in general, evaluation by internal rate of return (IRR) is not feasible, because multiple IRRs are involved. This paper deals with a problem of evaluating profitability, as well as risk, of investment alternatives made in multiple times of investment over the entire horizon. Typically, an additional investment is required after the initial one, for expanding manufacturing capacity or other reasons. The paper pays attention to a unit cash-flow over two periods, decomposing the total cash-flow into a series of unit cash-flow patterns. It is easy to evaluate profitability of a unit cash-flow by using IRR. The total cash-flow can be decomposed into the series of two types of unit cash-flows: an investment type one (negative-positive) and the borrowing type one (positive-negative). This paper, therefore, proposes a method in which only the borrowing type unit cash-flow is eliminated in the series by converting total cash-flow using capital interest rate. Then, a unique IRR can be obtained and the profitability is evaluated. Thus, the paper extends the method of IRR so that it may help decision making in complicated cash-flow pattern observed in practice.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.4
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• pp.31-41
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• 2003

This paper deals with a cell formation problem for a set of m-machines and n-processing parts. Generally, a cell formation problem is known as NP-completeness. Hence the cell formation problem with multiple objectives is more difficult than single objective problem. The paper considers multiple objectives; minimize number of intercell movements, minimize intracell workload variation and minimize intercell workload variation. We propose a multiple objective genetic algorithms(MOGA) resolving the mentioned three objectives. The MOGA procedure adopted Pareto optimal solution for selection method for next generation and the concept of Euclidean distance from the ideal and negative ideal solution for fitness test of a individual. As we consider several weights, decision maker will be reflected his consideration by adjusting high weights for important objective. A numerical example is given for a comparative analysis with the results of other research.

• ETRI Journal
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• v.38 no.4
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• pp.767-775
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• 2016

Automatic container code recognition from a captured image is used for tracking and monitoring containers, but often fails when the code is not captured clearly. In this paper, we increase the accuracy of container code recognition using multiple views. A character-level integration method combines recognized codes from different single views to generate a new code. A decision-level integration selects the most probable results from the codes from single views and the new integrated code. The experiment confirmed that the proposed integration works successfully. The recognition from single views achieved an accuracy of around 70% for the test images collected on a working pier, whereas the proposed integration method showed an accuracy of 96%.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.490-496
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• 1997

This paper describes a new process-plan selection method using a modified Fuzzy Quantification Theory(FQT). The problem of process-plan selection can be characterized by multiple attributes and used subjective, uncertain information. Fuzzy Quantification Theory is used for handling such information because it is a useful tool when human judgment or evaluation is quantified via linguistic variables, and the proposed method is concerned with the selection of a process plan by derivation of the values of categories for each attribute. In this paper, a modified Fuzzy Quantification Theory(FQT) is described and the procedure of this approach is explained and examples illustrated.

• Journal of Information Technology Applications and Management
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• v.25 no.1
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• pp.67-85
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• 2018

We propose a noise reduced risk aversion index for measuring risk aversion through a laboratory experiment to overcome disadvantages of the multiple pricing list format developed by Holt and Laury (2002). We use randomized multiple list choices with coarser classification and reward weighting, supplement the rank of risk aversion with extra individual characteristics of risk attitude, and construct an index of risk aversion by standardizing the risk aversion ranking with quantile normalization. Our method reduces multiple switching problems that noisy decision makers mistakenly commit in experimental approaches, so that it is free of the framing effect which severely occurred in the HL. Furthermore, the index doesn't utilize any specific utility function or probability weighting, which allows researcher to hold the independence axiom. Since our noise reduced index of risk aversion has many good traits, it is widely used and applied to reveal fundamental characteristics of risk-related behaviors in economics and finance regardless of experimental environment.

• Journal of the Korean Institute of Navigation
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• v.13 no.3
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• pp.37-44
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• 1989

Recently recognize the labor productivity of port physical distribution system in the port and shipping areas, Much Efforts for evaluating this productivity has been made continuously. BUt still there is little study, so far, on a systematic research for the management of port labor gangs, and even those were mainly depended on a rule of thumb. Especially the object of this study is to introduce the method of optimal allocation and assignment for the labor gangs per pier unit in the multiple ships berthed at an arbitary pier or port. In case the multiple ships have a homogeneous cargoes or do not have sufficient labor gangs to be assigned. The problem of optimal allocation and assignment of the labor gangs to be i) formalized with multi-state decision process in form of difference equation as the pattern which converted the independent multiple ships into a single ship with the intra-multiple ships, and ii) the optimal size of labor gangs could be obtained through the simple mathematical method instead of complicated dynamic programming, and iii) In case of shortage of labor gangs available the evaluation function considering the labor gangs available and total shift times was introduced, and iv) the optimal allocation and assignment of labor gangs was dealt at the point of minimizing the summation of the total shift times and at the point of minimizing the total cost charged for the extra waiting time except PHI time during port times for the multiple ships combinations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.897-904
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• 2006

Multiple input multiple output architectures, known to provide high spectral efficiencies, can provide the best performance in terms of the block error rate when a maximum likelihood (ML) detector is employed. The complexity of the ML detector, however, increases exponentially with the numbers of transmit antennas and signals in the constellation. The zero forcing (ZF) detector has been suggested as a reduced-complexity detection method at the cost of performance degradation. In order to improve the performance of the ZF detector while reducing the complexity of the ML detector, we propose a novel multistage decision method. Numerical results show that, despite the proposed detector has a lower complexity than the ML detector, the performance difference between the ML and proposed detectors is negligibly small at high SNR.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.877-884
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• 2011

The decision tree is a representative algorithm of data mining and used in many domains such as retail target marketing, fraud detection, data reduction, variable screening, category merging, etc. This method is most useful in classification problems, and to make predictions for a target group after dividing it into several small groups. When we create a model of decision tree with a large number of input variables, we suffer difficulties in exploration and analysis of the model because of complex trees. And we can often find some association exist between input variables by external variables despite of no intrinsic association. In this paper, we study on the removal method of unnecessary input variables using multiple external association rules. And then we apply the removal method to actual data for its efficiencies.

• Geomechanics and Engineering
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• v.24 no.5
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• pp.407-418
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• 2021

Due to the complexity of the causes of the sliding mass instabilities, landslide susceptibility and hazard evaluation are difficult, but they can be more carefully considered and regionally evaluated by using new programming technologies to minimize the hazard. This study aims to evaluate the landslide hazard zonation in the Tabriz region, Iran. A fuzzy logic-based multi-criteria decision-making method was proposed for susceptibility analysis and preparing the hazard zonation maps implemented in MATLAB programming language and Geographic Information System (GIS) environment. In this study, five main factors have been identified as triggering including climate (i.e., precipitation, temperature), geomorphology (i.e., slope gradient, slope aspect, land cover), tectonic and seismic parameters (i.e., tectonic lineament congestion, distribution of earthquakes, the unsafe radius of main faults, seismicity), geological and hydrological conditions (i.e., drainage patterns, hydraulic gradient, groundwater table depth, weathered geo-materials), and human activities (i.e., distance to roads, distance to the municipal areas) in the study area. The results of analyses are presented as a landslide hazard map which is classified into 5 different sensitive categories (i.e., insignificant to very high potential). Then, landslide susceptibility maps were prepared for the Tabriz region, which is categorized in a high-sensitive area located in the northern parts of the area. Based on these maps, the Bozgoosh-Sahand mountainous belt, Misho-Miro Mountains and western highlands of Jolfa have been delineated as risk-able zones.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.25-33
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• 2015

From the viewpoint of applications to manufacturing, data mining is a useful method to find the meaningful knowledge or information about states of processes. But the data from manufacturing processes usually have two characteristics which are multicollinearity and imbalance distribution of data. Two characteristics are main causes which make bias to classification rules and select wrong variables as important variables. In the paper, we propose a new data mining procedure to solve the problem. First, to determine candidate variables, we propose the multiple hypothesis test. Second, to make unbiased classification rules, we propose the decision tree learning method with different weights for each category of quality variable. The experimental result with a real PDP (Plasma display panel) manufacturing data shows that the proposed procedure can make better information than other data mining procedures.