• 한국CDE학회논문집
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• 제1권3호
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• pp.234-241
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• 1996

Recently, Genetic Algorithms(GAs), which consist of genetic operators named selection crossover and mutation, are widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GAs are very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GAs. So, they can be easily applicable to wide territory of design optimization problems. Also, virtue to multi-point search procedure, they have higher probability of convergence to global optimum compared with traditional techniques which take one-point search method. The introduction of basic theory on GAs, and the application examples in combination optimization of ten-member truss structure are presented in this paper.

• 디지털산업정보학회논문지
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• 제4권1호
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• pp.1-8
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• 2008

In the Web 2.0, besides more gaining information on the web, the number of web sites that take advantage of RSS increases explosively. Commonly each users search RSS channels through the web search engine before registering RSS channel's url to the RSS reader. Users judge whether the site is RSS channel or not and register an RSS channel's url through theirs interests. Because accomplished by users themselves, those processes conflict to user's convenience and quick consumption of information. Techniques of current search engines can't provide users with reliable RSS feed information as search results. In this paper, we analysis appropriateness of current search engines' techniques that offer users RSS feed search service and discuss their limitations. Also, we make up RSS feed database through classification of RSS tag being possible to search RSS feed information effectively and apply update rate of each RSS channel's feed to ranking algorithm providing more reliable search results.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권6호
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• pp.602-614
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• 2016

It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

• 한국CDE학회논문집
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• 제19권3호
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• pp.245-252
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• 2014

Engineering applications of global optimization techniques are recently abundant in the literature and it may be caused by both new methodologies arising and faster computers coming out. Many of the optimization techniques are based on natural or biological phenomena. This study put focus on enhancing the performace of Cuckoo Search (CS) among them since it has the least number of parameters to tune. The proposed enhancement can be achieved by applying surrogate-based optimization at every cycle of CS, which fortifies the exploitation capability of the original method. The enhanced algorithm has been applied several engineering design problems with constraints. The proposed method shows comparable or superior performance to the original method.

• Steel and Composite Structures
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• 제22권3호
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• pp.521-535
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• 2016

A Harmony Search (HS) and Genetic Algorithms (GA), two powerful metaheuristic search techniques, are used for minimum weight designs of different truss structures by selecting suitable profile sections from a specified list taken from American Institute of Steel Construction (AISC). A computer program is coded in MATLAB interacting with SAP2000-OAPI to obtain solution of design problems. The stress constraints according to AISC-ASD (Allowable Stress Design) and displacement constraints are considered for optimum designs. Three different truss structures such as bridge, dome and tower structures taken from literature are designed and the results are compared with the ones available in literature. The results obtained from the solutions for truss structures show that optimum designs by these techniques are very similar to the literature results and HS method usually provides more economical solutions in multi-element truss problems.

• BMB Reports
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• 제50권12호
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• pp.610-614
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• 2017

Scientists planning research that involves the use of animals are required to examine the possibilities for replacement, reduction, or refinement (the Three Rs), and their protocol must be reviewed by the Institutional Animal Care and Use Committee. Good scientific practice involving appropriate search techniques on the available Three Rs resources is essential for both ethical and scientific reasons. Appropriate experimental design and statistical analysis techniques are particularly necessary for research involving the use of animals, because this can improve animal welfare and scientific outcomes, as well as saving animal lives. There are a number of resources to help researchers improve their search techniques, experimental design strategies, and their reporting of research involving the use of animals. However, there is little specific information or resources on the Three Rs alternatives that is readily available in the Korean language. This paper outlines the common errors made by submitting researchers that have been repeatedly observed during the ethical review of experimental protocols over the last ten years, and provides information on the Korean resources available to promote good scientific practice. This could help to bridge the gap between Korean scientists and animal welfare advocates assisting scientists to improve ethical considerations and conduct responsible research.

• 대한조선학회논문집
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• 제42권2호
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• pp.175-182
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• 2005

It is necessary to develop an efficient optimization technique to optimize the engineering structures which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of engineering structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points by spreading point randomly entire the design spaces. In this paper, a Pareto optimal based multi-objective function method (PMOFM) is developed by considering the search direction based on Pareto optimal points, step size, convergence limit and random search generation . The PMOFM can also apply to the single objective function problems, and can consider the discrete design variables such as discrete plate thickness and discrete stiffener spaces. The design results are compared with existing Evolutionary Strategies (ES) method by performing the design of double bottom structures which have discrete plate thickness and discrete stiffener spaces.

• 한국정밀공학회지
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• 제14권12호
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• pp.24-29
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• 1997

Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.

• Structural Engineering and Mechanics
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• 제23권4호
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• pp.325-337
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• 2006

A hybrid structural design and optimization methodology that combines the strengths of genetic algorithms, local search techniques, and parallel computing is developed to evolve optimal truss systems in this research effort. The primary objective that is met in evolving near-optimal or optimal structural systems using this approach is the capability of satisfying user-defined design criteria while minimizing the computational time required. The application of genetic algorithms to the design and optimization of truss systems supports conceptual design by facilitating the exploration of new design alternatives. In addition, final shape optimization of the evolved designs is supported through the refinement of member sizes using local search techniques for further improvement. The use of the hybrid approach, therefore, enhances the overall process of structural design. Parallel computing is implemented to reduce the total computation time required to obtain near-optimal designs. The support of human-computer interaction during layout optimization and local optimization is also discussed since it assists in evolving optimal truss systems that better satisfy a user's design requirements and design preferences.

• 해양환경안전학회지
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• 제28권7호
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• pp.1231-1237
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• 2022

본 논문에서는 AI 기반 설계 탐색 기법을 활용하여 선박의 주요 치수 최적화를 수행하였다. 설계 탐색 기법은 최적화 프로그램 HEEDS의 SHERPA 알고리즘을 사용하였다. 유동 해석은 상용 CFD 코드인 STAR-CCM+를 사용하였고, 주요 치수 변환은 전처리 과정에서 JAVA Script와 Python을 사용하여 선박의 치수가 자동으로 변환되도록 설정하였다. 대상 선박은 소형 쌍동선형으로 주요 치수 최적화는 한쪽 선형의 길이, 폭, 흘수 그리고 단동선형 간의 간격에 대하여 수행되었다. 최적화 알고리즘에 사용된 목적함수는 총저항이며, 내부 의장 시스템의 크기 등을 고려한 배수 체적의 범위를 제한조건으로 선정하였다. 그 결과 최적 선형의 주요 치수는 기존 선형 대비 ±5% 내에서 변화가 있었고 총저항은 약 11% 개선된 결과를 보였다. 본 연구를 통해 선박의 형상을 직접 변경하지 않더라도 주요 치수 최적화를 통해 선박의 저항 성능이 향상됨을 확인하였고, 다양한 선박의 주요 치수 최적화를 통한 성능 향상에 활용이 될 것으로 기대한다.