• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.376-379
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• 2003

DNA computing based DNA sequence Is operated through the biology experiment. Biology experiment used as operator causes illegal reactions through shifted hybridization, mismatched hybridization, undesired hybridization of the DNA sequence. So, it is essential to design DNA sequence to minimize the potential errors. This paper proposes method of the DNA sequence generation based evolutionary operation processor. Genetic algorithm was used for evolutionary operation and extra hardware, namely genetic algorithm processor was implemented for solving repeated evolutionary process that causes much computation time. To show efficiency of the Proposed processor, excellent result is confirmed by comparing between fitness of the DNA sequence formed randomly and DNA sequence formed by genetic algorithm processor. Proposed genetic algorithm processor can reduce the time and expense for preparing DNA sequence that is essential in DNA computing. Also it can apply design of the oligomer for development of the DNA chip or oligo chip.

• 한국지능시스템학회논문지
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• 제12권4호
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• pp.317-322
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• 2002

The major operations of Evolutionary Computation include crossover, mutation, competition and selection. Although selection does not create new individuals like crossover or mutation, a poor selection mechanism may lead to problems such as taking a long time to reach an optimal solution or even not finding it at all. In view of this, this paper proposes a hybrid Evolutionary Programming (EP) algorithm that exhibits a strong capability to move toward the global optimum even when stuck at a local minimum using a synergistic combination of the following three basic ideas. First, a "local selection" technique is used in conjunction with the normal tournament selection to help escape from a local minimum. Second, the mutation step has been improved with respect to the Fast Evolutionary Programming technique previously developed in our research group. Finally, the crossover and mutation operations of the Genetic Algorithm have been added as a parallel independent branch of the search operation of an EP to enhance search diversity.

• 한국경영과학회지
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• 제37권3호
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• pp.39-55
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• 2012

This paper presents an endosymbiotic evolutionary algorithm (EEA) to solve both problems of line balancing and model sequencing in a mixed-model two-sided assembly line (MMtAL) simultaneously. It is important to have a proper balancing and model sequencing for an efficient operation of MMtAL. EEA imitates the natural evolution process of endosymbionts, which is an extension of existing symbiotic evolutionary algorithms. It provides a proper balance between parallel search with the separated individuals representing partial solutions and integrated search with endosymbionts representing entire solutions. The strategy of localized coevolution and the concept of steady-state genetic algorithms are used to improve the search efficiency. The experimental results reveal that EEA is better than two compared symbiotic evolutionary algorithms as well as a traditional genetic algorithm in solution quality.

• 한국식품영양학회지
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• 제31권2호
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• pp.272-277
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• 2018

This research was conducted to elucidate the optimum conditions for the antibacterial activity of konjak jelly using the evolutionary operation-factorial design technique. In the first set of experiments, concentration of a coagulation agent, soaking liquid, and temperature of water were set to 0.4%, $0.6{\times}10^{-2}N$, and $65^{\circ}C$ as a central point, respectively. The highest antibacterial activity was acquired at E21, in which the number of bacteria was 1.25 log cfu/g. Because the code of changes in the main effect was (-), it could be decided that the central point of the first set was not the optimum point. Although antibacterial activity in the second set was improved, the values of the main effect were higher than that of changes in the mean effect. The central point of third set was concentration of coagulation agent 0.8%, concentration of soaking liquid $1.0{\times}10^{-2}N$, and temperature of water $65^{\circ}C$. It was found that the antibacterial activity of central point in the third set was highest among all the tested set. Further, all the necessary conditions were appropriate to reach the optimum condition. The antibacterial activity of the central point in third set was more than 1,000 times higher than that of E11, in first set.

• Journal of Electrical Engineering and Technology
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• 제9권2호
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• pp.415-422
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• 2014

This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.

• Journal of the Korean Statistical Society
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• 제36권2호
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• pp.201-208
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• 2007

Evolutionary operation (EVOP) proposed by Box (1957) is a method for continuous monitoring and improvement of a full-scale manufacturing process with the objective of moving the operating conditions toward the better ones. EVOP consists of systematically making small changes in the levels of the two or three process variables under consideration. Data are collected on the response variable at each point of two level factorial design with the center point and a cycle is said to have been completed. The cycles are replicated sequentially until the decision is made on whether further cycle of experiments is needed to conclude the significance of any of main effects or interaction effects or the curvature. In this paper, an improved flow chart of EVOP is proposed and how to determine the number of cycles is studied based on the size of type II error. In order to reject the alternative hypothesis of interests with more confidence and conclude that we believe in the null hypothesis of no effects, we propose a counter measure $p^*-value$ corresponding to the p-value. The relationship of $p^*-value$ to the probability of type II error ${\beta}$ under the alternative hypothesis of interests is analogous to that of p-value to the probability of type I error ${\alpha}$. Also the implementation of EVOP with a mixture experiment is discussed.

• Food Science and Biotechnology
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• 제17권5호
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• pp.899-903
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• 2008

This study was conducted in order to elucidate the optimum conditions for the extraction of clove that can be used to elicit antibacterial activity against Streptococcus mutans using the evolutionary operation (EVOP)-factorial design technique. Higher antibacterial activity was achieved in a higher extraction temperature of $80^{\circ}C$ ($r=0.7983^{**}$) and in a longer extraction time of 26 hr ($r=0.6867^*$). Antibacterial activity was not effected by differentiation of ethanol concentration in the extraction solvent (r=-0.0683). The maximum antibacterial activity of clove against S. mutans as determined by the EVOP-factorial design technique was obtained at an extraction temperature of $80^{\circ}C$, an extraction time of 26 hr and a 50% ethanol concentration. Furthermore, the population of S. mutans decreased from an initial concentration of 6.850 to 4.195 log CFU/mL in the third set that is more than 2.6 log cycles by EVOP-factorial design technique.

• 대한전기학회논문지:전력기술부문A
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• 제50권7호
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• pp.318-323
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• 2001

This paper proposes an efficient method of On-Line Economic Load Dispatch(ELD) using Evolutionary Programming(EP) technique at KwangYang steel works. The economic operation of steel works is done by experienced engineer. So far, there is no formulation and algorithm of economic operation of steel works. In this paper, we propose the formulation and On-Line algorithm of economic operation of steel works. The EP technique is the kind of Evolutionary Computation(EC), which has become a candidate for many optimization applications due to its flexibility and efficiency. Based on the EP technique, the proposed algorithm is capable of not only solving the economic problem, but also obtaining the global optimal solutions within reasonable execution time. To validate our proposed approach, the algorithm is demonstrated on many sample systems and compared to actual values of steel works.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 A
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• pp.116-118
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• 2000

This paper proposes an efficient method of On-Line Economic Load Dispatch(ELD) using Evolutionary Programming(EP) technique at Kwangyang steel works. The economic operation of steel works is done by experienced engineer. So far, there is no formulation and algorithm of economic operation of steel works. In this paper, we propose the formulation and On-Line algorithm of economic operation of steel works. The EP technique is the kind of Evolutionary Computation(EC) which has become a candidate for many optimization applications due to its flexibility and efficiency. Based on the EP technique, the proposed algorithm is capable of not only solving the economic problem, but also obtaining the global optimal solutions within reasonable execution time. To validate our proposed approach, the algorithm is demonstrated on many sample systems and compared to actual values of steel works.

• 품질경영학회지
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• 제39권4호
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• pp.500-506
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• 2011

Evolutionary operation (EVOP) proposed by Box(1957) is a method for continuous monitoring and improvement of a full-scale manufacturing process with the objective of moving the current operating conditions toward the better ones. EVOP in experiments with mixtures consists of screening vital few components and making small changes in the current operating condition by making small increments in the proportion of the screened component. In this paper, how to determine operating conditions in EVOP in experiments with mixtures around the current operating condition is proposed. The proposed methods are illustrated with the simulated data based on the well known flare experimental data described by McLean and Anderson(1966).