• Journal of Korean Institute of Industrial Engineers
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• v.22 no.4
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• pp.533-549
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• 1996

This paper is concerned with a sequencing problem in mixed model assembly lines, which is important to efficient utilization of the lines. In the problem, we deal with the two objectives of minimizing the risk of stoppage and leveling part usage, and consider sequence-dependent setup time. In this paper, we present a genetic algorithm(GA) suitable for the multi-objective optimization problem. The aim of multi-objective optimization problems is to find all possible non-dominated solutions. The proposed algorithm is compared with existing multi-objective GAs such as vector evaluated GA, Pareto GA, and niched Pareto GA. The results show that our algorithm outperforms the compared algorithms in finding good solutions and diverse non-dominated solutions.

• IE interfaces
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• v.6 no.2
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• pp.117-131
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• 1993

A job sequencing model is developed and its computer system is tested for processing cold-rolled coils in Tandem Cold Mills(TCM) at the Pohang Iron and Steel Company. Given coils waiting to be processed, this system generates a sequence of jobs satisfying operational constraints for the TCM process. We formulate the problem as a constraint satisfaction problem and employ the backtracking technique combined with looking ahead features in order to generate a feasible solution within a reasonable time. Our system is implemented in C language on 80486-based IBM PC. Some tests based on the real data show that our system is adequate with respect to search time and that it consistantly generates a good feasible solution.

• Korean Journal of Breeding Science
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• v.43 no.2
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• pp.103-114
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• 2011

In recent years, genomic resources and information have accumulated at an ever increasing pace, in many plant species, through whole genome sequencing, large scale analysis of transcriptomes, DNA markers and functional studies of individual genes. Well-characterized species within key plant taxa, co-called "model systems", have played a pivotal role in nucleating the accumulation of genomic information and databases, thereby providing the basis for comparative genomic studies. In addition, recent advances to "Next Generation" sequencing technologies have propelled a new wave of genomics, enabling rapid, low cost analysis of numerous genomes, and the accumulation of genetic diversity data for large numbers of accessions within individual species. The resulting wealth of genomic information provides an opportunity to discern evolutionary processes that have impacted genome structure and the function of genes, using the tools of comparative analysis. Comparative genomics provides a platform to translate information from model species to crops, and to relate knowledge of genome function among crop species. Ultimately, the resulting knowledge will accelerate the development of more efficient breeding strategies through the identification of trait-associated orthologous genes and next generation functional gene-based markers.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.3
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• pp.280-285
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• 2004

This paper is concerned with the modeling and identification of sequencing batch reactor (SBR) via genetic algorithm based polynomial neural network (GA-based PNN). The model describes a biological SBR used in the wastewater treatment process fur nitrogen removal. A conventional polynomial neural network (PNN) is applied to construct a predictive model of SBR process fur nitrogen removal before. But the performances of PNN depend strongly on the number of input variables available to the model, the number of input variables and type (order) of the polynomials to each node. They must be fixed by the designer in advance before the architecture is constructed. So the trial and error method must go with heavy computation burden and low efficiency. To alleviate these problems, we propose GA-based PNN. The order of the polynomial, the number of input variables, and the optimum input variables are encoded as a chromosome and fitness of each chromosome is computed. Simulation results have shown that the complex SBR process can be modeled reasonably well by the present scheme with a much simpler structure compared with the conventional PNN model.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.411-420
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• 1999

A mixed model production line is a production line where a variety of product models are produced. In U-shaped production lines (called U-lines) used in just-in-time production system, the strategy of mixing product models is often used to provide various types of products to customers in time. Line balancing and model sequencing problems are important for an efficient use of mixed model U-lines. Although the two problems are tightly interrelated with each other, prior researches have considered them separately or sequentially. This paper presents a new method using a coevolutionary algorithm that can solve the two problems at the same time. To promote diversity and search efficiency, in this paper the evolutionary system is based on the localized interactions within and between populations. Methods of selecting environmental individuals and evaluating fitness are developed. Efficient genetic representations and operator schemes are also provided. When designing the schemes, we take into account the features specific to the problems. The experimental results demonstrate that the proposed algorithm is superior to existing approaches.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.558-558
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• 1992

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.34-35
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• 1999

• Journal of Microbiology and Biotechnology
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• v.33 no.9
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• pp.1162-1169
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• 2023

16S rRNA short amplicon sequencing-based microbiota profiling has been thought of and suggested as a feasible method to assess food safety. However, even if a comprehensive microbial information can be obtained by microbiota profiling, it would not be necessarily sufficient for all circumstances. To prove this, the feasibility of the most widely used V3-V4 amplicon sequencing method for food safety assessment was examined here. We designed a pathogen (Vibrio parahaemolyticus) contamination and/or V. parahaemolyticus-specific phage treatment model of raw oysters under improper storage temperature and monitored their microbial structure changes. The samples stored at refrigerator temperature (negative control, NC) and those that were stored at room temperature without any treatment (no treatment, NT) were included as control groups. The profiling results revealed that no statistical difference exists between the NT group and the pathogen spiked- and/or phage treated-groups even when the bacterial composition was compared at the possible lowest-rank taxa, family/genus level. In the beta-diversity analysis, all the samples except the NC group formed one distinct cluster. Notably, the samples with pathogen and/or phage addition did not form each cluster even though the enumerated number of V. parahaemolyticus in those samples were extremely different. These discrepant results indicate that the feasibility of 16S rRNA short amplicon sequencing should not be overgeneralized in microbiological safety assessment of food samples, such as raw oyster.

• Genomics & Informatics
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• v.20 no.4
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• pp.40.1-40.8
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• 2022

The concepts of phylogeny and floral genetics play a crucial role in understanding the origin and diversification of flowers in angiosperms. Angiosperms evolved a great diversity of ways to display their flowers for reproductive success with variations in floral color, size, shape, scent, arrangements, and flowering time. The various innovations in floral forms and the aggregation of flowers into different kinds of inflorescences have driven new ecological adaptations, speciation, and angiosperm diversification. Evolutionary developmental biology seeks to uncover the developmental and genetic basis underlying morphological diversification. Advances in the developmental genetics of floral display have provided a foundation for insights into the genetic basis of floral and inflorescence evolution. A number of regulatory genes controlling floral and inflorescence development have been identified in model plants such as Arabidopsis thaliana and Antirrhinum majus using forward genetics, and conserved functions of many of these genes across diverse non-model species have been revealed by reverse genetics. Transcription factors are vital elements in systems that play crucial roles in linked gene expression in the evolution and development of flowers. Therefore, we review the sex-linked genes, mostly transcription factors, associated with the complex and dynamic event of floral development and briefly discuss the sex-linked genes that have been characterized through next-generation sequencing.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.405-408
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• 2000

The objective of this paper is to develop a model to integrate process planning and resource planning through analysis of the machine tool selection and operations sequencing problem. The model is formulated as a travelling salesman problem with precedence relations. To solve our model, we also propose an efficient genetic algorithm based on topological sort concept.