• Journal of Construction Engineering and Project Management
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• v.7 no.2
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• pp.1-10
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• 2017

The Clonal Selection Algorithm (CSA) is an algorithm inspired by the human immune system mechanism. In CSA, several parameters needs to be optimized by large amount of sensitivity analysis for the optimal results. They limit the accuracy of the results due to the uncertainty and subjectivity. Adaptive Clonal Selection (ACS), a modified version of CSA, is developed as an algorithm without controls by pre-defined parameters in terms of selection process and mutation strength. In this paper, we discuss the ACS in detail and present its implementation in construction site utilization planning (CSUP). When applied to a developed model published in research literature, it proves that the ACS are capable of searching the optimal layout of temporary facilities on construction site based on the result of objective function, especially when the parameterization process is considered. Although the ACS still needs some improvements, obtaining a promising result when working on a same case study computed by Genetic Algorithm and Electimze algorithm prove its potential in solving more complex construction optimization problems in the future.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.345-358
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• 2012

In a parametric sample selection model, the distribution assumption is critical to obtain consistent estimates. Conventionally, the normality assumption has been adopted for both error terms in selection and main equations of the model. The normality assumption, however, may excessively restrict the true underlying distribution of the model. This study introduces the $S_U$-normal distribution into the error distribution of a sample selection model. The $S_U$-normal distribution can accommodate a wide range of skewness and kurtosis compared to the normal distribution. It also includes the normal distribution as a limiting distribution. Moreover, the $S_U$-normal distribution can be easily extended to multivariate dimensions. We provide the log-likelihood function and expected value formula based on a bivariate $S_U$-normal distribution in a sample selection model. The results of simulations indicate the $S_U$-normal model outperforms the normal model for the consistency of estimators. As an empirical application, we provide the sample selection model for car ownership and a car expense relationship.

• Genomics & Informatics
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• v.10 no.2
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• pp.81-87
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• 2012

Large-scale copy number variants (CNVs) in the human provide the raw material for delineating population differences, as natural selection may have affected at least some of the CNVs thus far discovered. Although the examination of relatively large numbers of specific ethnic groups has recently started in regard to inter-ethnic group differences in CNVs, identifying and understanding particular instances of natural selection have not been performed. The traditional $F_{ST}$ measure, obtained from differences in allele frequencies between populations, has been used to identify CNVs loci subject to geographically varying selection. Here, we review advances and the application of multinomial-Dirichlet likelihood methods of inference for identifying genome regions that have been subject to natural selection with the $F_{ST}$ estimates. The contents of presentation are not new; however, this review clarifies how the application of the methods to CNV data, which remains largely unexplored, is possible. A hierarchical Bayesian method, which is implemented via Markov Chain Monte Carlo, estimates locus-specific $F_{ST}$ and can identify outlying CNVs loci with large values of FST. By applying this Bayesian method to the publicly available CNV data, we identified the CNV loci that show signals of natural selection, which may elucidate the genetic basis of human disease and diversity.

• Journal of Industrial Convergence
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• v.18 no.2
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• pp.95-100
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• 2020

Among the customer-oriented data used to comprehend the customer, the user review data has received much attention as it provides insights into customer opinion in a detailed and large-scale manner; many customers have come to rely upon and trust the user reviews. Many application developers are cognizant of the importance of user reviews, so they monitor and respond to these reviews. However, due to the absence of a systematic method, developers have been investing their time and money without clear correlation to the customer satisfaction. Therefore, this paper suggests a systematic method to select user reviews from the application market using the Kano Model that deals with customer satisfaction and service quality, thereby maximizing the customer satisfaction under the given time period and budget. This method is constructed in the following phases: the user review collection and requirement elicitation phase in which the developers collect user reviews from the application market and elicit requirements, the Kano Model application and selection phase in which the Kano Model is applied to the elicited requirements and selection occurs based on the quality type, and the stakeholder review and redefinition phase in which relevant personnel gather to review and redefine requirements from an internal perspective.

• Journal of the Korean Operations Research and Management Science Society
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• v.17 no.3
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• pp.1-12
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• 1992

Parallel Genetic Algorithms (GAs) are developed to solve a single machine n-job scheduling problem which is to minimize the sum of absolute deviations of completion times from a common due date. (0, 1) binary scheme is employed to represent the n-job schedule. Two selection methods, best individual selection and simple selection are examined. The effect of crossover operator, due date adjustment mutation and due date adjustment reordering are discussed. The performance of the parallel genetic algorithm is illustrated with some example problems.

• Journal of the military operations research society of Korea
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• v.35 no.1
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• pp.63-82
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• 2009

The purpose of this study is to analyze the problems of current rules and regulations on the source selection for weapon system in defense acquisition project and suggest several techniques to ensure objectivity and fairness. As an application example, Helicopter source selection was presented. It was analyzed and compared through technique application and strength and weakness analysis of AHP, PROMETHEE and Attribute Transformation. The decision making techniques which make all conditions satisfactory in all situations are nonexistent. Thus, it is estimated that we can maintain the objectivity in the source selection of weapon systems by applying suitable decision making techniques in accordance with the patterns of evaluation item.

• Journal of Distribution Science
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• v.19 no.8
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• pp.25-35
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• 2021

Purpose: This study aims to propose an integrated MCDM model to support the qualified personnel selection in the distribution science. Research design, data, and methodology: The integrated approach of AHP and TOPSIS was employed to address the personnel selection problem. The AHP method was used to define the weights of the selection criteria, whereas the TOPSIS was applied to rank alternatives. The proposed model was then applied into a leading logistics company to select the best alternatives to be the sales deputy manager. Results: The results showed that Candidate 3 is the most qualified personnel for the sales deputy manager position as he is ranked first in the order of preference for recruitment. Conclusions: The proposed model provides the decision makers with more effective and time-saving methods than conventional ones. Therefore, the model can be applied to personnel selection around the world. In terms of theoretical contribution, this study proposes a personnel selection model for choosing the most appropriate candidates. In addition, the study adds to the theory of human resources management and logistics management the full set of personnel selection criteria including education, experience, skills, health, personality traits and foreign language.

• Journal for History of Mathematics
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• v.29 no.1
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• pp.17-30
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• 2016

This study focused on the selection and application of mathematical problems to provide mathematically challenging tasks for the gifted elementary students. For the selection, a mathematical problem from <算術管見> of Joseon dynasty, '圓容三方互求', was selected, considering the participants' experiences of problem solving and the variety of approaches to the problem. For the application, teaching strategies such as individual problem solving and sharing of the solving methods were used. The problem was provided for 13 mathematically gifted elementary students. They not only solved it individually but also shared their approaches by presentations. Their solving and sharing processes were observed and their results were analyzed. Based on this, some didactical considerations were suggested.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.1
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• pp.103-108
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• 2004

Companies adopted a program called Six Sigma, in order to make fundamental changes in the way the company operated to fulfill customers' expectations. Six Sigma reduces the occurrence of defects. This approach derives the overall process of selection the right projects based on their potential to improve performance metrics and selection and training the right people to get the business results. However, in the course of Six Sigma process steps, companies are in the face of problems. This study is to solve the problems using TOC(Theory of Constrains). TOC is methodology for solving key problem in system which is called Constraints. Nowadays, its application is going to be wide and its concept is being implemented. In this paper, it is showed possibility of application TOC to Six Sigma.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.146-150
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• 2003

Recently remote sensing technology is applied for construction projects planning and design areas by use of high resolution satellite images according to engineering application technology in the various experimental tasks. In this study, It was applied for optimum route selection methods and basic design by comparing to present railway and new expand dual railway route on the new construction plan path of 20 km at national railway lines, and then showed 3-dimensional images and fly simulation images to possibility for various application as low cost and short time compare to airplane and helicopters survey methods. As a results of its applied, It gained the results not only improvement of present methods but also real various application possibilities.