• Journal of Korean Association for Spatial Structures
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• v.8 no.3
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• pp.75-82
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• 2008

In this study, the modified genetic algorithm, D-GA, is proposed. D-GA is a hybrid genetic algorithm combined a simple genetic algorithm and the local search algorithm using direction vectors. Also, two types of direction vectors, learning direction vector and random direction vector, are defined without the sensitivity analysis. The accuracy of D-GA is compared with that of simple genetic algorithm. It is demonstrated that the proposed approach can be an effective optimization technique through a minimum weight structural optimization of ten bar truss.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.3
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• pp.17-24
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• 2013

Release planning in a software product line (SPL) is to select and assign the features of the multiple software products in the SPL in sequence of releases along a specified planning horizon satisfying the numerous constraints regarding technical precedence, conflicting priorities for features, and available resources. A greedy genetic algorithm is designed to solve the problems of release planning in SPL which is formulated as a precedence-constrained multiple 0-1 knapsack problem. To be guaranteed to obtain feasible solutions after the crossover and mutation operation, a greedy-like heuristic is developed as a repair operator and reflected into the genetic algorithm. The performance of the proposed solution methodology in this research is tested using a fractional factorial experimental design as well as compared with the performance of a genetic algorithm developed for the software release planning. The comparison shows that the solution approach proposed in this research yields better result than the genetic algorithm.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.140-146
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• 2019

Andrew Niccols's movie Gattaca (1997) inspired the formulation of the "Gattaca Argument" concerning the negative outcome of biotechnology, which has since been critiqued especially in the context of transhumanism and posthumanism. According this argument the development of genetic enhancement will produce a genetic discrimination and lead us to serious form of inequality. However, in particular transhumanists deny that here are reasons to worry and advocating instead the transformation of human condition in terms of genetic enhancement. Moreover, they question that genetic enhancement will necessarily lead to social inequality. In what follows, we will reexamine the Gattaca Argument and its critiques based on the movie in order to reassess the role the movie plays in the subsequent scholarly discussion. We will argue that existing critiques fall short of capturing the problem posed in the movie - the problem of the inhumane. Based on a hermeneutic approach to the movie we will both reconstruct the arguments and evaluate the transhuman counterarguments in terms of modern history of philosophical ideas.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.1
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• pp.33-41
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• 2011

This paper considers a topological optimization of a network design with mean packet delay and node connectivity constraints. The objective is to find the topological layout of links, at minimal cost. This Problem is known to be NP-hard. To efficiently solve the problem, a scatter search algorithm is proposed. An illustrative example is used to explain and test the proposal approach. Experimental results show evidence that the proposal approach performs more efficiently for finding a good solution or near optimal solution in comparison with a genetic approach.

• Journal of Nutrition and Health
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• v.34 no.1
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• pp.98-111
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• 2001

The article demonstrates a method of studying human health and nutrition by applying a multi-disciplinary approach and examines how humans developed and survived by adjusting to their environment. This process involves physiological, cultural and genetic adaptation both independently and interactively. This study postulates that a sound human health may be the result of balance between nutrition and environmental conditions. It is noted that there is a positive correlation between malaria and fava bean intake, and sickle cell anemia and cassava intake. It is also suggested that the difference in disease structure in soybean and non-soybean consumption cultures can be explained by an ecological approach to studying nutrition. This study further suggest that the relationship between nutrition and socio-cultural system. epidmiological study of nutrition and cultural environment nutrition and conceptual characteristics, nutrition and food intake pattern, nutrition and health sociological functions and the physioloical, cultural and genetic adaptation can all be stimulating research subjects to be studied form and ecological point of view. This article also includes the results from a series of ecological studies conducted by the author investigating the relationship between nutritional status of Korean breast-feeding mothers and the composition of the human milk and also the Vitamin D status of Korean and their lifestyle. (Korean J Nutrition 34(1):98-111, 2001)

• Journal of Electrical Engineering and Technology
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• v.8 no.5
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• pp.959-968
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• 2013

This paper presents a new approach with artificial immune system algorithm to solve the profit based unit commitment problem. The objective of this work is to find the optimal generation scheduling and to maximize the profit of generation companies (Gencos) when subjected to various constraints such as power balance, spinning reserve, minimum up/down time and ramp rate limits. The proposed hybrid method is developed through adaptive search which is inspired from artificial immune system and genetic algorithm to carry out profit maximization of generation companies. The effectiveness of the proposed approach has been tested for different Gencos consists of 3, 10 and 36 generating units and the results are compared with the existing methods.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.123-133
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• 1998

A cell design model based on operation sequence is proposed for maximizing the total parts flow within cells considering the data of Process plans for parts, Production volume, and cell size. A relationship between machines is calculated on the basis of the process plans for parts obtained from process plan sheets. Then the machines are classified into machine cells using the relationship. The model is formulated as a 0-1 integer programming and a genetic algorithm approach is developed to solve the model. The developed approach is tested and Proved using actual industrial data. Experimental results indicate that the approach is appropriate for large-size cell design problems efficiently.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.1
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• pp.82-88
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• 2007

This paper considers a topological optimization of a computer network design with a cost constraint. The objective is to find the topological layout of links, at maximal reliability, under the constraint that the network cost is less or equal than a given level of budget. This problem is known to be NP-hard. To efficiently solve the problem, a genetic approach is proposed. Two illustrative examples are used to explain and test the proposed approach. Experimental results show evidence that the proposed approach performs more efficiently for finding a good solution or near optimal solution in comparison with a simulated annealing method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.2
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• pp.81-88
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• 2010

This paper presents an application of heuristic approach to problem of designing reliable network expansion. The problem essentially consists in finding the network topology that satisfies given set of reliability constraints. To efficiently solve the problem, a scatter search approach is proposed. The results of the two experiments show that scatter search is a more suitable approach for finding a good solution or near optimal solution in comparison with genetic algorithm.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1009-1011
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• 1996

This paper presents an approach to building multi-input and single-output fuzzy models for nonlinear data-based systems. Such a model is composed of fuzzy rules, and its output is inferred by simplified reasoning. Optimal structure and membership parameters for a fuzzy model are automatically and simultaneously identified by GA(Genetic Algorithm). Numerical examples are provided to evaluate the feasibility of the proposed approach. Comparison shows that the suggested approach can produce a fuzzy model with higher accuracy and a smaller number of fuzzy rules than the ones achieved previously in other methods.