• 식물분류학회지
• /
• 제49권4호
• /
• pp.324-333
• /
• 2019

Neutral genetic diversity found in plant species usually leaves an indelible footprint of historical events. Korea's main mountain range (referred to as the Baekdudaegan [BDDG]), is known to have served as a glacial refugium primarily for the boreal and temperate flora of northeastern Asia. In addition, life-history traits (life forms, geographic range, and breeding systems) influence the within- and among-population genetic diversity of seed plant species. For example, selfing species harbor significantly less within-population genetic variation than that of predominantly outcrossers. A previous study of two Liparis species (L. makinoana and L. kumokiri) emphasizes the role of the abovementioned factors shaping the levels of genetic diversity. Liparis makinoana, mainly occurring on the BDDG and self-incompatible, harbors high levels of within-population genetic diversity (expected heterozygosity, H_eP = 0.319), whereas there is no allozyme variation (H_eP = 0.000) in L. kumokiri, which is self-compatible and mainly occurs in lowland hilly areas. To determine if this trend is also found in other congeners, we sampled five populations of L. krameri from the southern part of the Korean Peninsula and investigated the allozyme-based genetic diversity at 15 putative loci. The somewhat intermediate levels of within-population genetic variation (H_eP = 0.145) found in L. krameri are most likely due to its occurrence in mountainous areas that, despite being outside of the main ridge of the BDDG, still served as refugia, and a self-incompatible breeding system. Management strategies are suggested for L. krameri and L. makinoana based on the levels and distribution of genetic diversity and inbreeding.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
• /
• pp.167-170
• /
• 2004

This paper proposes resource allocation method for achieving investment goals in manufacturing system. In order to align resource allocation and manufacturing system design, the system design decomposition (SDD) approach is used. In this paper, a mathematical formulation for resource allocation based on SDD approach is analyzed and a genetic algorithm application is discussed.

• Journal of applied mathematics & informatics
• /
• 제25권1_2호
• /
• pp.217-229
• /
• 2007

In this paper, Genetic Algorithm (GA) is used to find the Maximum Weight Independent Set (MWIS) of a graph. First, MWIS problem is formulated as a 0-1 integer programming optimization problem with linear objective function and a single quadratic constraint. Then GA is implemented with the help of this formulation. Since GA is a heuristic search method, exact solution is not reached in every run. Though the suboptimal solution obtained is very near to the exact one. Computational result comprising an average performance is also presented here.

• International Journal of Control, Automation, and Systems
• /
• 제2권1호
• /
• pp.100-106
• /
• 2004

In this paper, we present a novel, rapid approach for the detection of brain tumors and deformity boundaries in medical images using a genetic algorithm with wavelet based preprocessing. The contour detection problem is formulated as an optimization process that seeks the contour of the object in a manner of minimizing an energy function based on an active contour model. The brain tumor segmentation contour, however, cannot be detected in case that a higher gradient intensity exists other than the interested brain tumor and deformities. Our method for discerning brain tumors and deformities from unwanted adjacent tissues is proposed. The proposed method can be used in medical image analysis because the exact contour of the brain tumor and deformities is followed by precise diagnosis of the deformities.

• 대한산업공학회지
• /
• 제40권6호
• /
• pp.642-647
• /
• 2014

In this paper, a hybrid genetic algorithm (HGA) approach is proposed for an n-job, m-machine flow shop scheduling problem with limited capacity buffers with blocking in which the objective is to minimize the total stretch. The stretch of a job is the ratio of the amount of time the job spent before its completion to its processing time. HGA adopts the idea of seed selection and development in order to improve the exploitation and exploration power of genetic algorithms (GAs). Extensive computational experiments have been conducted to compare the performance of HGA with that of GA.

• Journal of Information Processing Systems
• /
• 제11권2호
• /
• pp.239-247
• /
• 2015

Cryptography aims at transmitting secure data over an unsecure network in coded version so that only the intended recipient can analyze it. Communication through messages, emails, or various other modes requires high security so as to maintain the confidentiality of the content. This paper deals with IDEA's shortcoming of generating weak keys. If these keys are used for encryption and decryption may result in the easy prediction of ciphertext corresponding to the plaintext. For applying genetic approach, which is well-known optimization technique, to the weak keys, we obtained a definite solution to convert the weaker keys to stronger ones. The chances of generating a weak key in IDEA are very rare, but if it is produced, it could lead to a huge risk of attacks being made on the key, as well as on the information. Hence, measures have been taken to safeguard the key and to ensure the privacy of information.

• 한국IT서비스학회지
• /
• 제18권5호
• /
• pp.155-164
• /
• 2019

With the emergence of new ICT technologies, information security threats are becoming more advanced, intelligent, and diverse. Even though the awareness of the importance of information security increases, the information security budget is not enough because of the lack of effectiveness measurement of the information security investment. Therefore, it is necessary to optimize the information security investment in each business environment to minimize the cost of operating the information security countermeasures and mitigate the damages occurred from the information security breaches. In this paper, using genetic algorithms we propose an investment optimization model for information security countermeasures with the limited budget. The optimal information security countermeasures were derived based on the actual information security investment status of SMEs. The optimal solution supports the decision on the appropriate investment level for each information security countermeasures.

• 전자공학회논문지B
• /
• 제33B권5호
• /
• pp.138-151
• /
• 1996

This paper proposes a genetic fuzzy controller ensemble (FCE) for improving the control performance of of fuzzy controller in the non-linear and complex problems. The design procedure of each fuzzy controller in the FCF consists of the following two stages, each of which is performed by different genetic algorithms. The first stage generates a fuzzy rule base that covers the training examples as many as possible. The second stage builds fine-tuned membership funcitons that make the control error as small as possible. These two stages are repeated independently upon the different partition patterns of input-output variables. The control performance of the proposed method is compared with that of wang and mendel's approach[1] in terms of either the percentage of successful controls reaching to the goal or the average traveling distance.

• 산업경영시스템학회지
• /
• 제20권42호
• /
• pp.171-179
• /
• 1997

Genetic Algorithms face an inherent conflict between exploitation and exploration. Exploitation refers to taking advantage of information already obtained in the search. Exploration show that a pattern in bits coupled with another pattern elsewhere in the string is more effective. In this paper shows that the selection method has a major impact on the balance between exploitation and exploration. A more heavy-handed approach seeks to exploit the available information. If decisions must be made quickly, especially those in real-time trading environments, then quicker convergence through exploitation may be more desirable. Also this paper we present some theoretical and empirical the selection method in genetic algorithms for a GA-hard problem.

• 한국지능시스템학회논문지
• /
• 제8권6호
• /
• pp.58-69
• /
• 1998

This paper introduces a novel neuro-fuzzy system based on the polynomial fuzzy neural network(PFNN) architecture. The PFNN consists of a set of if-then rules with appropriate membership functions whose parameters are optimized via a hybrid genetic algorithm. A polynomial neural network is employed in the defuzzification scheme to improve output performance and to select appropriate rules. A performance criterion for model selection, based on the Group Method of DAta Handling is defined to overcome the overfitting problem in the modeling procedure. The hybrid genetic optimization method, which combines a genetic algorithm and the Simplex method, is developed to increase performance even if the length of a chromosome is reduced. A novel coding scheme is presented to describe fuzzy systems for a dynamic search rang in th GA. For a performance assessment of the PFNN inference system, three well-known problems are used for comparison with other methods. The results of these comparisons show that the PFNN inference system outperforms the other methods while it exhibits exceptional robustness characteristics.