• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.569-572
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• 2000

DEA has been effectively applied to various areas which need the evaluation of relative efficiency. We propose a DEA model based on fuzzy LP combined with Genetic Algorithm in order to consider uncertain synergy effects due to M&A of existing organization. We apply the suggested approach to forecasting the efficiency of merged academic departments in a university in Korea. We expect that our approach can be utilized to effectively realign existing departments.

• 한국산업정보학회논문지
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• 제22권2호
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• pp.79-89
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• 2017

본 연구에서는 적응형혼합유전알고리즘(Adaptive Hybrid Genetic Algorithm: AHGA) 접근법을 이용한 폐쇄루프 공급망(Closed-Loop Supply Chain: CLSC) 모델 최적화를 다루고 있다. CLSC 모델 구축을 위해 공급업체(Part Supplier), 제품제조업체(Product Manufacturer)등으로 구성된 전방향물류(Forward Logistics)와 수집업체(Collection Center), 회복센터(Recovery Center)등으로 구성된 역물류(Reverse Logistics)를 함께 고려하고 있다. 제안된 CLSC 모델은 수리모형(Mathematical Model)으로 표현되며, AHGA접근법을 이용해 이행되어 그 최적해를 구하게 된다. 수치실험에서는 기존연구에서 제안된 몇몇 접근법과 AHGA 접근법을 함께 사용하여 그 수행도를 비교분석하였다.

• 대한안전경영과학회지
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• 제22권4호
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• pp.65-74
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• 2020

Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.946-949
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• 2005

It is very a time-consuming and error-prone process to obtain the optimal injection condition, which can produce good injection molding products in some operational variation of facilities, from a seed injection condition. This study proposes a new approach to search the optimal injection molding condition using a neural network and a genetic algorithm. To estimate the defect type of unknown injection conditions, this study forces the neural network into learning iteratively from the injection molding conditions collected. Major two parameters of the injection molding condition - injection pressure and velocity are encoded in a binary value to apply to the genetic algorithm. The optimal injection condition is obtained through the selection, cross-over, and mutation process of the genetic algorithm. Finally, this study compares the optimal injection condition searched using the proposed approach. with the other ones obtained by heuristic algorithms and design of experiment technique. The comparison result shows the usability of the approach proposed.

• 대한유전성대사질환학회지
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• 제23권2호
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• pp.1-7
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• 2023

유전성 대사질환은 생화학적 대사 이상에 의해 발생하는 질환 군으로, 매우 다양할 뿐만 아니라 임상 양상이 서로 겹칠 수 있어 진단에 어려움을 겪을 수 있다. 과거에는 유전성 대사질환의 원인이 될 수 있는 유전자를 선정한 후 한 개씩 분석하는 방식으로 유전자 검사를 시행했다. 하지만, 최근에는 차세대 염기서열분석 기술이 발전함에 따라 유전성 대사질환과 관련된 수백-수천개의 유전자를 한꺼번에 분석하거나, 인간의 모든 유전자를 포함하는 엑솜/게놈 분석을 시행한 후 원인 유전자를 찾는 방식으로 유전 진단의 패러다임이 바뀌고 있다. 본 종설에서는 차세대 염기서열분석을 이용한 유전성 대사질환의 유전 진단 방법과 진단율 및 주의점 등을 살펴보고자 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권4호
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• pp.217-222
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• 2011

Genetic algorithms are one of the most important methods used to solve the Traveling Salesman Problem. Therefore, many researchers have tried to improve the Genetic Algorithm by using different methods and operations in order to find the optimal solution within reasonable time. This paper intends to find a new approach that adopts an improved genetic algorithm to solve the Traveling Salesman Problem, and compare with the well known heuristic method, namely, Kohonen Self-Organizing Map by using different data sets of symmetric TSP from TSPLIB. In order to improve the search process for the optimal solution, the proposed approach consists of three strategies: two separate tour segments sets, the improved crossover operator, and the improved mutation operator. The two separate tour segments sets are construction heuristic which produces tour of the first generation with low cost. The improved crossover operator finds the candidate fine tour segments in parents and preserves them for descendants. The mutation operator is an operator which can optimize a chromosome with mutation successfully by altering the mutation probability dynamically. The two improved operators can be used to avoid the premature convergence. Simulation experiments are executed to investigate the quality of the solution and convergence speed by using a representative set of test problems taken from TSPLIB. The results of a comparison between the new approach using the improved genetic algorithm and the Kohonen Self-Organizing Map show that the new approach yields better results for problems up to 200 cities.

• 한국산업정보학회논문지
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• 제25권6호
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• pp.159-169
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• 2020

본 연구에서는 중국에서 유통되고 있는 냉장식품 (-1℃ to 8℃)에 대한 콜드체인 물류(Cold chain logistics: CCL) 모델이 개발되었다. CCL 모델은 분배센터 (Distribution center: DC)와 배포대상지점 (Distribution target points: DT)으로 구성되어 있으며, CCL 모델의 목적함수는 모든 유통업체의 총 유통경로를 최소화하는 것이다. 목적함수를 통한 최적결과 도출을 위해 혼합유전알고리즘(Hybrid genetic algorithm: HGA) 접근법을 제안한다. HGA 접근법은 개선된 K-means 방법과 유전알고리즘을 결합하여 구성된다. 사례연구에서는 유통경로와 유통 가능한 거리 기준으로 CCL 모델에 대해 3개의 시나리오를 고려하였으며, 이를 제안된 HGA접근법을 사용하여 해결하였다. 결과분석을 통해 제안된 HGA접근법을 사용할 경우 유통비용이 절감되고, 마일리지가 약 19%, 20%, 16% 정도 감소됨을 확인하였다.

• 품질경영학회지
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• 제32권4호
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• pp.125-139
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• 2004

Generally, parallel redundancy is used to improve reliability in many systems. However, redundancy increases system cost, weight, volume, power, etc. Due to limited availability of these resources, the system designer has to maximize reliability subject to various constraints or minimize resources while satisfying the minimum requirement of system reliability. This paper presents GAs (Genetic Algorithms) to solve redundancy allocation in series-parallel systems. To apply the GAs to this problem, we propose a genetic representation, the method for initial population construction, evaluation and genetic operators. Especially, to improve the performance of GAs, we develop heuristic operators (heuristic crossover, heuristic mutation) using the reliability-resource information of the chromosome. Experiments are carried out to evaluate the performance of the proposed algorithm. The performance comparison between the proposed algorithm and a pervious method shows that our approach is more efficient.

• 산업공학
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• 제19권4호
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• pp.300-305
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• 2006

The problem of assigning customers to satellite channels is considered in this paper. Finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is shown to be NP-complete in an earlier study. We propose a genetic algorithm (GA) approach to search for the best/optimal assignment of customers to satellite channels. Various issues related to genetic algorithms such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. A comparison of GA with CPLEX8.1 is presented to show the advantages of this approach in terms of computation time and solution quality.

• 대한수학교육학회지:학교수학
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• 제5권4호
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• pp.401-420
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• 2003

증명 학습에 있어서 많은 어려움이 특히, 증명이 도입되는 중학교 기하 단원의 학습에서 야기되고 있으며, 무엇보다도 많은 학생들이 증명의 의미를 이해하지 못하는 것은 간과하기 어려운 문제점이다. 본 고에서는 기하의 역사 발생적 단계에 따른 증명의 의미 지도가 증명 지도 개선을 위한 하나의 방안이 될 수 있음을 밝히고자 하였다. Branford가 제시한 바와 같이 역사-발생적 전개를 통하여 증명의 의미를 지도하는 방안을 모색해 보고자, Euclid원론이 성립하기까지의 기하의 역사적 발달 과정과 병행하여 실험적, 직관적, 과학적 단계를 거쳐 발전되어 온 증명의 발생 과정을 살펴보고 지도 과정을 분석해 보았다. 그리고 실험적, 직관적 증명 단계를 거쳐 수학적인 증명을 도입하는 지도 과정에 따라 삼각형의 내각의 합에 대한 명제의 증명 지도를 중학교 1학년 학생들을 대상으로 실시해 보았다. 본 고에서는 그러한 결과를 통하여 역사-발생적 접근이 학생들에게 증명의 의미를 이해시키는데 큰 도움이 된다는 것을 확인하였다.