• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.11
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• pp.938-943
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• 2013

In this paper, we propose a transmission parameter optimization scheme based on genetic algorithm for dynamic spectrum access systems. Specifically, we represent a multiple objective fitness function as a weighted sum of single objective fitness functions to optimize transmission parameters, and then, obtain optimized transmission parameters based on genetic algorithm for given transmission scenarios. From numerical results, we confirm that the transmission parameters are well optimized by using the proposed optimization scheme.

• Journal of Korean Association for Spatial Structures
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• v.4 no.4 s.14
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• pp.91-98
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• 2004

Genetic algorithm is one of the best ways to solve a discrete variable optimization problem. This method is an unconstrained optimization technique, so the constraints are handled in an implicit manner. The most popular way of handling constraints is to transform the original constrained problem into an unconstrained problem, using the concept of penalty function. I present the 3 fitness functions which represent the reject strategy, the penalty strategy, and the combined strategy. I make the design program using the 3 fitness Auctions and it is applied to the design problem of a gable frame and a 2 story 3 span frame.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.4
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• pp.9-16
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• 2010

In the health monitoring of civil engineering structures, the optimal sensor placement has a major influence on the quality of the results. This paper considers the problem of locating sensors with the aim of maximizing the data information so that structural parameters or damage of structures can be assessed. An proposed technique using a genetic algorithm is introduced to find the optimal placement of sensors. The sensitivity on modal vectors by structural parameters and the orthogonality of modal vectors have been taken as the fitness function of the genetic algorithm. A simple tower structure is used for example analyses to investigate the feasibility and applicability of the proposed approach. The example analyses show the way how the modal sensitivity and the modal orthogonality in the fitness function have influence on the optimal sensor placement. It is shown that the present method using the proposed fitness function can provide the reliable results.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.439-447
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• 2003

This paper proposes a proportional-integral-derivative (PID) evaluation method for enhancing performance of genetic algorithms. In PID evaluation, the fitness of individuals is evaluated by not only the fitness derived from an evaluation function, but also the parents fitness of each individual and the minimum and maximum fitness from initial generation to previous generation. This evaluation decreases the probability that the genetic algorithms fall into a premature convergence phenomenon and results in enhancing the performance of genetic algorithms. We experimented our evaluation method with typical numerical function optimization problems. It was found from extensive experiments that out evaluation method can increase the performance of genetic algorithms greatly. This evaluation method can be easily applied to the other types of genetic algorithms for improving their performance.

• Journal of Ocean Engineering and Technology
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• v.27 no.5
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• pp.28-35
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• 2013

In this paper, a research on the composition of the nesting algorithm fitness function is carried out by performing various numerical experiments to inspect how it affects the scrap efficiency, allocation characteristics, and time consumption, targeting the nesting results of ship parts. This paper specifically concentrates on a method to minimize the scrap ratio and efficiently use the well-defined remnants of a raw plate after the nesting process for the remnant nesting. Therefore, experiments for various ship parts are carried out with the weighting factor method, one of the multi-objective optimum design methods. Using various weighting factor sets, the nesting results are evaluated in accordance with the above purposes and compared with each set for each ship part groups. Consequently, it is suggested that the nesting algorithm fitness function should be constructed differently depending on the characteristics of the parts and the needs of the users.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.1
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• pp.90-100
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• 1999

유전자 알고리즘은 전통적인 등반 알고리즘을 이용하여 구하기 어려웠던 최적화 문제를 해결하기 위한 강인한(Robust) 탐색 기법이다. 특히 목적함수가 (1)여러 개의 국부 최대치를 가지는 경우, (2)수학적으로 표현이 불가능하거나 어려운 경우, (3)목적함수에 교란 항(disturbance term)이 섞여 있을 경우도 우수한 탐색 능력을 갖는 것으로 알려져 있다. 본 논문에서는 유전자 알고리즘을 이용하여 나타나는 다양한 해집합을 형성하는 개체군을 군집성 분석(cluster analysis)을 이용하여 군집화하고, 각 군집에 부여된 군집 적합도에 따라서 최적해를 구함으로써 단순 유전자 알고리즘에 의한 최적화보다 훨씬 향상된 탐색 알고리즘을 제안하였다. 반응표면의 형태가 정형화한 테스트 함수의 형태로 나타난다고 가정한 경우에 대하여 몬테 칼로 시뮬레이션을 통하여 본 알고리즘을 적용하여 평가하고 분석하였다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.60-67
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• 2011

Since the non-metric Multidimensional scaling (nMDS), a data visualization technique, provides with insights about engineering, economic, and scientific applications, it is widely used for analyzing large non-metric multidimensional data sets. The nMDS requires a fitness function to measure fit of the proximity data by the distances among n objects. Most commonly used fitness functions are nonlinear and have a difficulty to find a good configuration. In this paper, we propose a new fitness function, an absolute value type, and show its advantages.

• Journal of KIISE:Information Networking
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• v.36 no.1
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• pp.50-56
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• 2009

This paper proposes a new algorithm of clustering similar nodes defined as nodes having similar characteristic values in pure P2P environment. To compare similarity between nodes, we introduce a fitness function whose return value depends only on the two nodes' characteristic values. The higher the return value is, the more similar the two nodes are. We propose a GORGFM algorithm newly in conjunction with the fitness function to recommend and exchange nodes' characteristic values for an interest group formation and maintenance. With the GORGFM algorithm, the interest groups are formed dynamically based on the similarity of users, and all nodes will highly satisfy with the information recommended and received from nodes of the interest group. To evaluate of performance of the GORGFM algorithm, we simulated a matching rate by the total number of nodes of network and the number of iterations of the algorithm to find similar nodes accurately. The result shows that the matching rate is highly accurate. The GORGFM algorithm proposed in this paper is highly flexible to be applied for any searching system on the web.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.78-84
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• 1998

In this paper, a fuzzy traffic controller using genetic algorithms is presented. Conventional fuzzy traffic controllers use membership functions generated by humans. However, this approach does not guarantee the optimal solution to design the fuzzy controller. Genetic algorithm is a good problem solving method requiring domain-specific knowledge that is often heuristic. To find fuzzy membership functions showing good performance, a fitness function must be defined. However it's not easy in traffic control to define such a function as a numeric expression. Thus, we use simulation approach, namely, the fitness value of a solution is determined by use of a performance measure that is obtained by traffic simulator. The proposed method outperforms the conventional fuzzy controllers.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.365-367
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• 2003

염기서열 디자인은 DNA computing, 샘물정보학 등의 분야에서 실험 설계시 고려해야할 중요한 문제 중의 하나이다. 이 문제는 다양한 조건을 만족시키는 최적의 염기서열 집합을 생성하는 조합 최적화 문제로 생각될 수 있으며, 염기서열이 갖추어야 할 조건을 적합도 함수로 사용한 진화 연산 등의 방법이 적용되어 왔다. 본 논문에서는 여러 논문들에서 제시된 적합도 함수의 구체적인 형태를 해 공간상에서 조사해 보았으며, 각 적합도 함수간의 관계도 분석해 보았다.