• 한국지능시스템학회논문지
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• 제11권3호
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• pp.191-199
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• 2001

유전자알고리듬(Genetic Algorithm)은 확률적인 집단 탐색법이고 적응도함수의 형태에 관계없는 직접 탐색법이기 때문에 최근 최적화 방법으로 주목을 받고 있다. 본 논문에서는 Job-shop Schedule Problem에 대하여 교배방법으로 JOX를 사용하며, 효율적인 탐색을 위하여 탐색범위를 축소시키는 강제조작을 형질유전을 고려한 형질유전GT법을 제안하고, 세대교체에 있어 모집단의 다양성을 유지하기 위하여 집단 내에 동일한 개체를 배제하는 방법을 제안한다. 제안 알고리듬을 Fisher & Thompson의 FT10$\times$10 및 FT20$\times$5 문제에 적용하여 유효성을 실험적으로 검증한다.

• 대한기계학회논문집A
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• 제26권9호
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• pp.1806-1813
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• 2002

It is well known that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a classical optimization technique was adopted by previous researchers. That technique overcame the difficulty of finding the intersection point of the superposed contours that correspond to the eigenfrequency caused by the crack presence. However, it is hard to select a trial solution initially for optimization because the defined objective function is heavily multimodal. A method is presented in this paper, which uses continuous evolutionary algorithms(CEAs). CEAs are effective for solving inverse problems and implemented on PC clusters to shorten calculation time. With finite element model of the structure to calculate eigenfrequencies, it is possible to formulate the inverse problem in optimization format. CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising with high parallel efficiency over about 94%.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.99-101
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• 2000

DNA 컴퓨팅 기법은 실제 생체 분자(bio-molecule)를 계산의 도구로 사용하는 새로운 계산 방법으로, 진화 연산과 결합하여 인공지능의 새로운 분야로 부각되고 있다. 그러나, 실제 생체 분자를 계산의 도구로 사용하기 때문에 기존의 컴퓨터에 적용하기 어렵고, 단순히 합성과 분리라는 간단한 방법으로 해를 구하기 때문에 보다 효과적인 알고리즘을 개발하여야 할 필요성이 있다. 따라서, 본 논문에서는 DNA 컴퓨팅 기법을 컴퓨터에 적용하기 위한 방법으로 DNA 컴퓨팅에서의 코드 합성 기법과 유전자 알고리즘을 이용하여 NP-complete 문제중의 하나인 Sub-Set Sum 문제를 해결하여 그 결과를 분석한다. Sub-Set Sum 문제에서 단순 유전자 알고리듬보다 DNA 코드 유전자 알고리즘이 높은 성능을 보인다.

• 대한산업공학회지
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• 제37권1호
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• pp.1-9
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• 2011

This paper presents a new method that can solve the integrated problem of combined location routing and inventory problem (CLRIP) efficiently. The CLRIP is used to establish facilities from several candidate depots, to find the optimal set of vehicle routes, and to determine the inventory policy in order to minimize the total system cost. We propose a mathematical model for the CLRIP with budget constrained. Because this model is a nonpolynomial (NP) problem, we propose a endosymbiotic evolutionary algorithm (EEA) which is a kind of symbiotic evolutionary algorithm (SEA). The heuristic method is used to obtaining the initial solutions for the EEA. The experimental results show that EEA perform very well compared to the existing heuristic methods with considering inventory control decisions.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.59-71
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• 2005

In this paper we address a design problem for hub and spoke transportation networks and then consider a capacitated hub locations problem with direct shipment (CHLPwD). We determine the location of hubs, the allocation of nodes to hubs, and direct shipment paths in the network, with the objective of minimizing the total cost in the network. An evolutionary algorithm is developed here to solve the CHLPwD. To do this, we propose the representation and the genetic operators suitable for the problem and adopt a heuristic method for the allocation of nodes to hubs. To enhance the search capability, problem-specific information is used in our evolutionary algorithm. The proposed algorithm is compared with the heuristic method in terms of solution quality and computation time. The experimental results show that our algorithm can provide better solutions than the heuristic.

• 한국경영과학회지
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• 제25권4호
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• pp.67-80
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• 2000

Symbiotic evolutionary algorithms, also called cooperative coevolutionary algorithms, are stochastic search algorithms that imitate the biological coevolution process through symbiotic interactions. In the algorithms, the fitness evaluation of an individual required first selecting symbiotic partners of the individual. Several partner selection strategies are provided. The goal of this study is to analyze how much partnering strategies can influence the performance of the algorithms. With two types of test-bed problems: the NKC model and the binary string covering problem, extensive experiments are carried out to compare the performance of partnering strategies, using the analysis of variance. The experimental results indicate that there does not exist statistically significant difference in their performance.

• 산업공학
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• 제12권4호
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• pp.540-550
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• 1999

In evolutionary algorithm, there exist various models for the evolution of the population with respect to schemes and strategies for reproduction. In the application of the algorithm to a specific problem, one model suitable to the problem is to be properly chosen and a program expert or a software is needed to help implement and test a designed algorithm. In this study, the software for simple evolutionary algorithms(SEA) with one population is developed. The software is designed as an application framework type, so that it may be friendly, allow users to add some program, and operate under the environment of Windows. For this, hierarchical classes for components of SEA are first designed by means of an object-oriented approach and then a library for SEA is built by them. With the library, developed is an application framework that can generate a frame code for an application program. The software proposed here can be used as a generalized tool for solving problems in a wide range of domains.

• 대한산업공학회지
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• 제31권1호
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• pp.10-19
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• 2005

The minimum spanning tree (MST) problem is one of the traditional optimization problems. Unlike the MST, the degree constrained minimum spanning tree (DCMST) of a graph cannot, in general, be found using a polynomial time algorithm. So, finding the DCMST of a graph is a well-known NP-hard problem of importance in communications network design, road network design and other network-related problems. So, it seems to be natural to use evolutionary algorithms for solving DCMST. Especially, when applying an evolutionary algorithm to spanning tree problems, a representation and search operators should be considered simultaneously. This paper introduces a new tree representation scheme and a genetic operator for solving combinatorial tree problem using evolutionary algorithms. We performed empirical comparisons with other tree representations on several test instances and could confirm that the proposed method is superior to other tree representations. Even it is superior to edge set representation which is known as the best algorithm.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2003년도 추계학술대회 및 정기총회
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• pp.166-169
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• 2003

일정한 시간이 지나면 제품으로서의 가치가 사라지게 되는 단일기간 재고품목들은 생산된 직후 전량 각 고객들에게 주어진 납기에 맞추어 효율적인 분배가 요구된다. 본 연구에서는 고객들은 다수 종류의 제품을 주문할 수 있으며 제품종류별 분리배송을 허용하는 상황에서 생산비, 수송비, 납기위반비, 차량고정비를 최소화하기 위한 생산순서 및 차량경로를 수립함을 목적으로 한다. 이에 대한 해법으로써 진화개미해법을 개발하였다. 개발된 해법의 성능평가를 위해 각 고객의 위치, 주문 제품 종류, 주문량들을 다르게 하여 구축한 실험문제에 대하여 유전알고리듬해법과 비교실험을 수행하였다.

• 경영과학
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• 제17권2호
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• pp.75-86
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• 2000

In evolutionary algorithm, there exist various models for the evolution of the population with respect to schemes and strategies for reproduction. In the application of the algorithm to a specific problem, one model suitable to the problem is to be properly chosen and a program expert or a software is needed to help implement and test a designed algorithm. In this study, abject oriented modeling and the class library for simple evolutionary algorithms(SEA) with one population is developed. The library proposed here can be used as a generalized tool for solving problems in a wide range of domains.