• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.3
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• pp.149-155
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• 2005

In this paper, we optimize simulation model of a manufacturing system using the real-coded genetic algorithm. Because the manufacturing system expressed by simulation model has stochastic process, the objective functions such as the throughput of a manufacturing system or the resource utilization are not optimized by simulation itself. So, in order to solve it, we apply optimization methods such as a genetic algorithm to simulation method. Especially, the genetic algorithm is known to more effective method than other methods to find global optimum, because the genetic algorithm uses entity pools to find the optimum. In this study, therefore, we apply the real-coded genetic algorithm to simulation optimization of a manufacturing system, which is known to more effective method than the binary-coded genetic algorithm when we optimize the constraint problems. We use the reproduction operator of the applied real-coded genetic algorithm as technique of the remainder stochastic sample with replacement and the crossover operator as the technique of simple crossover. Also, we use the mutation operator as the technique of the dynamic mutation that configures the searching area with generations.

• Journal of Ecology and Environment
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• v.43 no.4
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• pp.454-461
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• 2019

Background: Ikonnikov's whiskered bat (Myotis ikonnikovi) is found throughout the Korean Peninsula, as well as in Kazakhstan, Russia, Mongolia, China, and Japan. It is small-sized and primarily inhabits old-growth forests. The decrease and fragmentation of habitats due to increased human activity may influence the genetic structure of bat populations. This study was designed to elucidate the population genetic structure of M. ikonnikovi using mitochondrial genes (cytochrome oxidase I and cytochrome b). Results: The results showed that M. ikonnikovi populations from Korea have high genetic diversity. Although genetic differentiation was not detected for the COI gene, strong genetic differentiation of the Cytb gene between Mt. Jeombong and Mt. Jiri populations was observed. Moreover, the results indicated that the gene flow of the maternal lineage may be limited. Conclusions: This study is the first to identify the genetic population structure of M. ikonnikovi. We suggest that conservation of local populations is important for sustaining the genetic diversity of the bat, and comprehensive studies on factors causing habitat fragmentation are required.

• Biomedical Science Letters
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• v.30 no.2
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• pp.65-72
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• 2024

The national diabetes and prediabetes prevalence rate has risen among Korean adolescents and adults. Type 2 diabetes mellitus (T2DM) is commonly interrelated with genetic, metabolic, and environmental risk factors in clinical practice. In this study, we analyzed the association between genetic polymorphisms of the ABO gene with T2DM in the Korean population, we conducted an analysis of gene-phenotype correlation, based on an additive genetic model. A total of 8,840 subjects from the Korea Association REsource (KARE) were selected for this study. Using the genetic and epidemiologic data of 754 T2DM cases and 5721 normal controls from the KARE, single nucleotide polymorphisms (SNPs) in the ABO gene were analyzed for their genetic correlation. As a result, 8 SNPs out of the ABO gene demonstrated statistically significant association with T2DM. Among them, rs657152 in the ABO gene statistically showed the most significant correlation with T2DM (P-value=0.0084, OR=1.15, CI=1.04~1.28). The minor allele of A polymorphism within the intron genetic region of ABO directed increased risk of T2DM. This work reveals a significant association between genetic polymorphism in the ABO gene and T2DM. This finding suggested that ABO SNPs markers might be a genetic correlation to the etiology of T2DM.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.125-139
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• 2004

Generally, parallel redundancy is used to improve reliability in many systems. However, redundancy increases system cost, weight, volume, power, etc. Due to limited availability of these resources, the system designer has to maximize reliability subject to various constraints or minimize resources while satisfying the minimum requirement of system reliability. This paper presents GAs (Genetic Algorithms) to solve redundancy allocation in series-parallel systems. To apply the GAs to this problem, we propose a genetic representation, the method for initial population construction, evaluation and genetic operators. Especially, to improve the performance of GAs, we develop heuristic operators (heuristic crossover, heuristic mutation) using the reliability-resource information of the chromosome. Experiments are carried out to evaluate the performance of the proposed algorithm. The performance comparison between the proposed algorithm and a pervious method shows that our approach is more efficient.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.7
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• pp.1129-1134
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• 1999

The rapid development of the sheep genetic linkage map over the last five years has given us the ability to follow the inheritance of chromosomal regions. Initially this powerful resource was used to find markers linked to monogenic traits but there is now increasing interest in using the genetic linkage map to define the complex of genes that control multigenic production traits. Of particular interest are those production traits that are difficult to measure and select for using classical quantitative genetic approaches. These include resistance to disease where a disease challenge (necessary for selection) poses too much risk to valuable stud animals and meat and carcass qualities which can be measured only after the animal has been slaughtered. The goal for the new millennium will be to fully characterise the genetic basis of multigenic production traits. The genetic linkage map is a vital tool required to achieve this.

• 한국약용작물학회:학술대회논문집
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• 2011.09a
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• pp.364-365
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• 2011

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2350-2353
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• 2009

For applications that are grid enabled, the grid can offer a resource balancing effect by scheduling grid jobs on machines with low utilization. When jobs communicate with each other, the internet, with storage resources, an advanced scheduler could schedule them to minimize communications traffic or minimize the distance of the communications. We propose an load redistribution algorithm to minimize communication traffic and distance of the communication using genetic algorithm. The experiments show the proposed load redistribution algorithm performs efficiently in the variance of load in grid environments.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.89-100
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• 2016

Given the unpredictability of the space environment, satellite communications are manually performed by exchanging telecommands and telemetry. Ground support for orbiting satellites is given only during limited periods of ground antenna visibility, which can result in conflicts when multiple satellites are present. This problem can be regarded as a scheduling problem of allocating antenna support (task) to limited visibility (resource). To mitigate unforeseen errors and costs associated with manual scheduling and mission planning, we propose a novel method based on a genetic algorithm to solve the ground support problem of multiple satellites and antennae with visibility conflicts. Numerous scheduling parameters, including user priority, emergency, profit, contact interval, support time, remaining resource, are considered to provide maximum benefit to users and real applications. The modeling and formulae are developed in accordance with the characteristics of satellite communication. To validate the proposed algorithm, 20 satellites and 3 ground antennae in the Korean peninsula are assumed and modeled using the satellite tool kit (STK). The proposed algorithm is applied to two operation modes: (i) telemetry, tracking, and command and (ii) payload. The results of the present study show near-optimal scheduling in both operation modes and demonstrate the applicability of the proposed algorithm to actual mission control systems.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.171-180
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• 2009

Population learning algorithm (PLA) is a population-based method that was inspired by the similarities to the phenomenon of social education process in which a diminishing number of individuals enter an increasing number of learning stages. The study aims to develop a framework that repeatedly applying the PLA to solve the discrete resource constrained project scheduling problem with two objectives: minimizing project makespan and renewable resource availability, which are two most common concerns of management when a project is being executed. The PLA looping framework will provide a number of near Pareto optimal schedules for the management to make a choice. Different improvement schemes and learning procedures are applied at different stages of the process. The process gradually becomes more and more sophisticated and time consuming as there are less and less individuals to be taught. An experiment with ProGen generated instances was conducted, and the results demonstrated that the looping framework using PLA outperforms those using genetic local search, particle swarm optimization with local search, scatter search, as well as biased sampling multi-pass algorithm, in terms of several performance measures of proximity. However, the diversity using spread metric does not reveal any significant difference between these five looping algorithms.

• Journal of Environmental Science International
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• v.11 no.11
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• pp.1149-1156
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• 2002

The ecological characteristics of Dolbae trees, a valuable genetic resource for native pyrus fruit trees, were investigated at four naturally inhabited areas on Mount Kaya, Gyeongsangnam-Do. Most Dolbae trees were found on the southwest side of an old hiking path to a mountain valley at altitudes of 610∼670 m. The surrounding flora consisted of 46 families, 69 genera, 75 species, and 10 varieties. The natural habitat of the Dolbae trees was basically a deciduous broad-leaved forest with a predominance of Quercus serrata and ligneous plants(xylophytes) from the Fagaceae and Betulaceae families. The habitat was also found to be in a second transition resulting from forest disturbance and exhibited a degree of diversity of 2.901-5.065, based on Shannon-Weiner's index. Examination of the Dolbae trees found in Mount Kaya revealed diameter breast heights(DBHs) ranging from 10 to 60 cm, including six old and large Dolbae trees with a DBH of 50∼60 cm, which will be particularly valuable as a genetic resource. Accordingly, the current results suggest that the study areas are a secondary forest in a typical mid-temperate zone resulting from forest damage about 10 years earlier.