• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2004년도 추계학술대회
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• pp.171-178
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• 2004

This study suggests a general paradigm enhancing genetic mutability. Mutability among heterogeneous members in a genetic population has been a major problem in application of genetic programming to diverse business problems. This suggested paradigm is implemented to developing new methods from existing methods. Within the evolutionary approach taken to designing new methods, a general representation scheme of the genetic programming framework, called a kernel, is introduced. The kernel is derived from the literature of algorithms and heuristics for combinatorial optimization problems. The commonality and differences among these methods have been identified and again combined by following the genetic inheritance merging them. The kernel was tested for selected methods in combinatorial optimization. It not only duplicates the methods in the literature, it also confirms that each of the possible solutions from the genetic mutation is in a valid form, a running program. This evolutionary method suggests diverse hybrid methods in the form of complete programs through evolutionary processes. It finally summarizes its findings from genetic simulation with insight.

• 한국정밀공학회지
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• 제15권12호
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• pp.72-80
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• 1998

In this study, a design approach based on genetic algorithm is proposed to solve the manufacturing cell design problem considering alternative process plans and alternative machines. The problem is formulated as a 0-1 integer programming model which considers several manufacturing parameters, such as demand and processing time of part, machine capacity, manufacturing cell size, and the number of machines in a machine cell. A genetic algorithm is used to determine process plan for each part, part family and machine cell simultaneously.

• Journal of information and communication convergence engineering
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• 제3권4호
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• pp.209-212
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• 2005

This study proposes hybrid case-based reasoning and genetic algorithms model for customer classification. In this study, vertical and horizontal dimensions of the research data are reduced through integrated feature and instance selection process using genetic algorithms. We applied the proposed model to customer classification model which utilizes customers' demographic characteristics as inputs to predict their buying behavior for the specific product. Experimental results show that the proposed model may improve the classification accuracy and outperform various optimization models of typical CBR system.

• Structural Engineering and Mechanics
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• 제60권3호
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• pp.413-431
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• 2016

A sensitivity analysis estimates the effect of the change in the uncertain variable parameter on the probability of the structural failure. A novel fuzzy random reliability sensitivity measure of the failure probability is proposed to consider the effect of the epistemic and aleatory uncertainties. The uncertainties of the engineering variables are modeled as fuzzy random variables. Fuzzy quantities are treated using the ${\lambda}$-cut approach. In fact, the fuzzy variables are transformed into the interval variables using the ${\lambda}$-cut approach. Genetic approach considers different possible combinations within the search domain (${\lambda}$-cut) and calculates the parameter sensitivities for each of the combinations.

• 경영과학
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• 제17권2호
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• pp.55-65
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• 2000

This paper addresses a problem of machining route selection in multi-stage process with machine group. This problem is considered the subcontracting and the production in-house such as regular and overtime work. the proposed model is formulated as a 0-1 integer programming constraining the avaliable time of each machine for planning period and total overtimes. The objective of the model is to minimize the sum of processing cost, overtime cost, and subcontracting cost. To solve this model, a genetic algorithm(GA) approach is developed. The effectiveness of the proposed GA approach is evaluated through comparisons with the optimal solution obtained from the branch and bound. In results, the same optimal solution is obtained from two methods at small size problem, and the consistent solution is provided by the GA approach at large size problem. The advantage of the GA approach is the flexibility into decision-making process because of providing multiple machining routes.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2000년도 춘계정기학술대회 e-Business를 위한 지능형 정보기술 / 한국지능정보시스템학회
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• pp.343-346
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• 2000

In this paper, a novel approach to intruder detection is introduced. The approach, based on the genetic algorithms, improved detection rate of the host systems which has traditionally relied on known intruder patterns and host addresses. Rather than making judgments on whether the access is instrusion or not, the systems can continuously monitor systems with categorized security level. With the categorization, when the intruder attempts repeatedly to access the systems, the security level is incrementally escalated. In the simulation of a simple intrusion, it was shown that the current approach improves robustness of the security systems by enhancing detection and flexibility. The evolutionary approach to intruder detection enhances adaptability of the system.

• Communications for Statistical Applications and Methods
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• 제14권3호
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• pp.531-540
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• 2007

When multiple objectives exist, there are three approaches exist. These are maximin design, compound design, and constrained design. Still, each of three design criteria has its own strength and weakness. In this paper Hybrid approach is suggested when multiple design objectives exist, which is a combination of maximin and constrained design. Sometimes experimenter has several objectives, but he/she has only one or two primary objectives, others less important. A new approach should be useful under this condition. The genetic algorithm is used for few examples. It has been proven to be a very useful technique for this complex situation. Conclusion follows.

• Structural Engineering and Mechanics
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• 제68권5호
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• pp.549-561
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• 2018

Sobol method is applied as a powerful variance decomposition technique in the field of global sensitivity analysis (GSA). The paper is devoted to increase convergence speed of the extracted Sobol indices using a new proposed sampling technique called genetic based Latine hypercube sampling (GBLHS). This technique is indeed an improved version of restricted Latine hypercube sampling (LHS) and the optimization algorithm is inspired from genetic algorithm in a new approach. The new approach is based on the optimization of minimax value of LHS arrays using manipulation of array indices as chromosomes in genetic algorithm. The improved Sobol method is implemented to perform factor prioritization and fixing of an uncertain comprehensive high speed rotor-bearing system. The finite element method is employed for rotor-bearing modeling by considering Eshleman-Eubanks assumption and interaction of axial force on the rotor whirling behavior. The performance of the GBLHS technique are compared with the Monte Carlo Simulation (MCS), LHS and Optimized LHS (Minimax. criteria). Comparison of the GBLHS with other techniques demonstrates its capability for increasing convergence speed of the sensitivity indices and improving computational time of the GSA.

• 한국정보통신학회논문지
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• 제15권6호
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• pp.1251-1255
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• 2011

본 논문에서는 최적화 문제를 해결하는 기법의 하나인 유전자 알고리즘을 이용하여 모든 노드를 탐색하여 최적의 경로를 도출하는 최적화 경로 탐색 알고리즘을 제안한다. 경로를 도출하기 위해 중간 경로 노드로부터 출발지 노드 및 도착지 노드까지의 거리를 측정하여 개체를 생성한다. 출력 노드들을 도출하기 위해 생성된 개체를 적합도 함수에 적용하여 적합도를 계산한다. 계산된 적합도 값에 따라 교배를 할 노드 및 교배 지점(비트단위)을 선택한다. 선택된 노드와 교배 지점을 이용하여 개체들을 교배한다. 교배를 통해 새로운 개체를 생성한다. 새로운 개체가 적합도 조건에 만족하면 출력 노드로 도출하고, 다음 출력 노드를 도출할 때의 출발지 노드로 선택한다. 이러한 과정을 반복하여 모든 출력 노드를 도출한다. 제안된 방법을 실험한 결과, 순차 방식과 난수를 이용한 경우보다 제안된 방법이 효율적인 것을 확인하였다.

• 한국산학기술학회논문지
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• 제11권6호
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• pp.2269-2275
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• 2010

유전자 알고리즘은 매개변수와 유전자 연산자 그리고 계획과 같은 다양한 요인들에 의해 영향을 받으며, 전통적인 방법을 통한 문제의 해결은 효율적이지만 전체적으로는 실행 가능성의 문제와 결과의 도출에 걸리는 시간의 문제가 있을 수 있다. 이에 따라 전통적인 유전자 알고리즘은 다양한 방법으로 수정 및 적용되어 질 수 있다. 본 연구는 Travelling Salesman 문제를 해결하기 위해 초기에 정렬된 인자를 사용하여 수정된 유전자 알고리즘을 적용하였다. 본 연구를 통한 접근 방법은 초기 문제의 크기를 줄이며 또한 빠른 복합 수렴을 달성하였다. 또한 제안된 방법은 객체지향 접근을 사용한 시뮬레이터를 통해 테스트 되었고 그 결과는 제안된 방법의 타당성을 입증하였다.