• 한국강구조학회 논문집
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• 제13권5호
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• pp.577-586
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• 2001

이 연구에서는 다 셀계수변수와 다 제약조건으로 구성된 단면 및 시스템 형상을 동시에 고려하는 입체 트러스의 이산화 최적설계 문제를 유전자 알고리즘을 이용하여 체계화하였다. 또한 유전자 알고리즘의 적용방법을 초기화절차 진화적 절차 그리고 유전적 절차로 구성하였다. 초기화 절차에서는 한 세대의 개체 수만큼 염색체를 생성하고 진화적 절차는 구조해석의 결과를 분석하여 적합도를 계산하였다. 그리고 유전적 절차는 복제와 교배 및 돌연변이를 통하여 다음 세대의 유전자를 생성하게 된다. 이렇게 진화적 절차와 유전적 절차를 반복 수행하여 최적 해를 탐색한다. 이 연구에서는 설계자가 궁극적 목표로 하는 구조물의 구조 해석과 단면 및 시스템 형상 최적설계를 동시에 수행할 수 있는 이산화 최적설계 프로그램을 개발하고 설계 예를 들어 비교 고찰하였다.

• 한국경영과학회지
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• 제24권3호
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• pp.73-82
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• 1999

In this paper, we address a single machine non-preemptive n-job scheduling problem to minimize the sum of earliness and tardiness with different release times and due dates. To solve the problem, we propose a genetic algorithm with new crossover and mutation operators to find the job sequencing. For the proposed genetic algorithm, the optimal pair of crossover and mutation rates is investigated. To illustrate the suitability of genetic algorithm, solutions of genetic algorithm are compared with solutions of exhaustive enumeration method in small size problems and tabu search method in large size problems. Computational results demonstrate that the proposed genetic algorithm provides the near-optimal job sequencing in the real world problem.

• 산업경영시스템학회지
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• 제26권4호
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• pp.23-30
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• 2003

This study develops an efficient heuristic which is based on genetic approach for AGVs flow path layout problem. The suggested solution approach uses a algorithm to replace two 0-1 integer programming models and a branch-and-bound search algorithm. Genetic algorithms are a class of heuristic and optimization techniques that imitate the natural selection and evolutionary process. The solution is to determine the flow direction of line in network AGVs. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. Genetic algorithm procedure is suggested, and a simple illustrative example is shown to explain the procedure.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1996년도 추계학술대회발표논문집; 고려대학교, 서울; 26 Oct. 1996
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• pp.45-48
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• 1996

The most research on facility layout problems ignored the actual shape of building where the activities(departments) are to be arranged. They also ignored the aisles between departments inside the building. In this paper, we present a genetic algorithm that searches a very good facility layout with horizontal aisles for two different cases with respect to the department shape. From the extensive experiments, the proposed genetic algorithm generated better layouts than the ones obtained by applying Tam's algorithm. It showed about 10% improvement of performance. We found out the best combination of genetic operators through the experiments.

• 반도체디스플레이기술학회지
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• 제13권2호
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• pp.23-28
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• 2014

For the reconstruction of three-dimensional (3D) shape of microscopic objects through shape from focus (SFF) methods, usually a single focus measure operator is employed. However, it is difficult to compute accurate depth map using a single focus measure due to different textures, light conditions and arbitrary object surfaces. Moreover, real images with diverse types of illuminations and contrasts lead to the erroneous depth map estimation through a single focus measure. In order to get better focus measurements and depth map, we have combined focus measure operators by using genetic algorithm. The resultant focus measure is obtained by weighted sum of the output of various focus measure operators. Optimal weights are obtained using genetic algorithm. Finally, depth map is obtained from the refined focus volume. The performance of the developed method is then evaluated by using both the synthetic and real world image sequences. The experimental results show that the proposed method is more effective in computing accurate depth maps as compared to the existing SFF methods.

• 산업경영시스템학회지
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• 제27권2호
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• pp.102-113
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• 2004

This paper addresses the transportation planning that is based on genetic algorithm for determining transportation time and transportation amount of minimizing cost of distribution system. The vehicle routing of minimizing the transportation distance of vehicle is determined. A distribution system is consisted of a distribution center and many retailers. The model is assumed that the time horizon is discrete and finite, and the demand of retailers is dynamic and deterministic. Products are transported from distribution center to retailers according to transportation planning. Cost factors are the transportation cost and the inventory cost, which transportation cost is proportional to transportation distance of vehicle when products are transported from distribution center to retailers, and inventory cost is proportional to inventory amounts of retailers. Transportation time to retailers is represented as a genetic string. The encoding of the solutions into binary strings is presented, as well as the genetic operators used by the algorithm. A mathematical model is developed. Genetic algorithm procedure is suggested, and a illustrative example is shown to explain the procedure.

• 정보처리학회논문지B
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• 제18B권3호
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• pp.157-164
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• 2011

본 논문은 유전자 알고리즘을 이용해서 동적으로 변하는 네트워크상에서 빠르게 최단 경로를 재탐색할 수 있는 알고리즘을 제안한다. 제안 알고리즘은 다익스트라 알고리즘과 유전자 알고리즘을 통합한 형식의 알고리즘이다. 이 제안 알고리즘은 최초 탐색 시 다익스트라(Dijkstra) 알고리즘을 이용해서 유전자 알고리즘의 초기화 과정을 용이하게 하는 선행자 배열을 정의한다. 그 후 유전자 알고리즘은 적절한 유전 연산자를 통해 동적으로 변하는 트래픽 상황에서 최적의 경로를 재탐색한다. 실험 결과를 통해 제안 알고리즘이 거대한 네트워크 데이터에 대해서 다른 유전자 알고리즘 기반의 최단경로 찾기 알고리즘이나 다익스트라 알고리즘보다 적은 계산시간으로 더 짧은 주행시간의 경로를 제시한다는 것을 보였다.

• 대한산업공학회지
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• 제25권3호
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• pp.360-368
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• 1999

We consider the problem of scheduling n jobs with sequence-dependent processing times on a set of parallel-identical machines. The processing time of each job consists of a pure processing time and a sequence-dependent setup time. The objective is to maximize the total remaining machine available time which can be used for other tasks. For the problem, a hybrid genetic algorithm is proposed. The algorithm combines a genetic algorithm for global search and a heuristic for local optimization to improve the speed of evolution convergence. The genetic operators are developed such that parallel machines can be handled in an efficient and effective way. For local optimization, the adjacent pairwise interchange method is used. The proposed hybrid genetic algorithm is compared with two heuristics, the nearest setup time method and the maximum penalty method. Computational results for a series of randomly generated problems demonstrate that the proposed algorithm outperforms the two heuristics.

• 한국경영과학회지
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• 제25권2호
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• pp.101-114
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• 2000

Multicasting is the simultaneous transmission of data to multiple destinations. In multicast ATM networks the effect of failures on transmission links or nodes can be catastrophic so that the issue of survivability is of great importance. However little attention has been paid to the problem of multicast restoration. This paper presents an efficient heuristic technique for routing backup virtual paths in ulticast networks with link failure. Genetic algorithm is employed here as a heuristic. In the application of genetic algorithm to the problem, a new genetic encoding and decoding method and genetic operators are proposed in this paper. The other several heuristics are also presented in order to assess the performance of the proposed algorithm. Experimental results demonstrate that our algorithm is a promising approach to solving the problem.

• Steel and Composite Structures
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• 제4권6호
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• pp.453-469
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• 2004

In this article, a genetic algorithm based optimum design method is presented for non-linear steel frames with semi-rigid connections. The design algorithm obtains the minimum weight frame by selecting suitable sections from a standard set of steel sections such as European wide flange beams (i.e., HE sections). A genetic algorithm is employed as optimization method which utilizes reproduction, crossover and mutation operators. Displacement and stress constraints of Turkish Building Code for Steel Structures (TS 648, 1980) are imposed on the frame. The algorithm requires a large number of non-linear analyses of frames. The analyses cover both the non-linear behaviour of beam-to-column connection and $P-{\Delta}$ effects of beam-column members. The Frye and Morris polynomial model is used for modelling of semi-rigid connections. Two design examples with various type of connections are presented to demonstrate the application of the algorithm. The semi-rigid connection modelling results in more economical solutions than rigid connection modelling, but it increases frame drift.