• 한국해양공학회지
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• 제17권6호
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• pp.53-57
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• 2003

Optimum design of most structural system requires that design variables are regarded as discrete quantities. This paper presents the use of Genetic Algorithm for determining the optimum design for truss with discrete variables. Genetic Algorithm are know as heuristic search algorithms, and are effective global search methods for discrete optimization. In this paper, Elitism and the method of conferring penalty parameters in the design variables, in order to achieve improved fitness in the reproduction process, is used in the Genetic Algorithm. A 10-Bar plane truss and a 25-Bar space truss are used for discrete optimization. These structures are designed for stress and displacement constraints, but buckling is not considered. In particular, we obtain continuous solution using Genetic Algorithms for a 10-bar truss, compared with other results. The effectiveness of Genetic Algorithms for global optimization is demonstrated through two truss examples.

• 한국강구조학회 논문집
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• 제17권4호통권77호
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• pp.385-394
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• 2005

본 논문은 유전자알고리즘과 퍼지이론에 근거한 개선된 퍼지-유전자알고리즘에 의한 이산화 최적설계 프로그램을 개발하였다. 본 연구의 최적설계는 평면 및 입체 강구조물의 단면, 형상 최적설계가 동시에 수행된다. 본 연구에서 목적함수는 강구조물의 중량이고, 제약조건식은 설계 및 좌굴강도, 변위 및 부재단면의 두께에 대한 설계제한식이다. 설계변수는 철골부재 단면의 치수와 절점좌표이다. 그리고 본 연구의 개선된 퍼지-유전자 알고리즘에 의한 이산화 최적설계 프로그램의 적용을 위해 설계 예를 들었다.

• 한국해양공학회지
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• 제23권6호
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• pp.131-135
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• 2009

We present an optimum design method for a rectangular reinforced concrete beam using Genetic Algorithms. The optimum design procedure in this paper employs 2 design cases: i) all of the design variables (b, d, As) of the rectangular reinforced concrete section are used pseudo-continuously, ii) one is pseudo-continuous for the concrete cross section (b, d) and the other is discrete, using an index for the steel area (As). The optimum design in this paper uses Chakrabarty's model. In this paper, the Genetic Algorithms use the method of Elitism and penalty parameters to improve the fitness in the reproduction process, which leads to very practical designs. The optimum design of the steel area in the examples uses ASTM standard reinforcing bars (#3~#11, #14, #18).

• Structural Engineering and Mechanics
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• 제27권5호
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• pp.575-588
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• 2007

In this paper, two algorithms are presented for the optimum design of geometrically nonlinear steel space frames using tabu search. The first algorithm utilizes the features of short-term memory (tabu list) facility and aspiration criteria and the other has long-term memory (back-tracking) facility in addition to the aforementioned features. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Allowable stress design (ASD) specification, maximum drift (lateral displacement) and interstorey drift constraints were imposed on the frames. The algorithms were applied to the optimum design of three space frame structures. The designs obtained using the two algorithms were compared to each other. The comparisons showed that the second algorithm resulted in lighter frames.

• 산업경영시스템학회지
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• 제22권49호
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• pp.115-123
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• 1999

An optimization problem is to select the best of many possible design alternatives in a complex design space. Genetic algorithms, one of the numerous techniques to search optimal solution, have been successfully applied to various problems (for example, parameter tuning in expert systems, structural systems with a mix of continuous, integer and discrete design variables) that could not have been readily solved with more conventional computational technique. But, conventional genetic algorithms are ill defined for two classes of problems, ie., penalty function and fitness scaling. Therefore, this paper develops Improved genetic algorithms(IGA) to solve these problems. As a case study, numerical examples are demonstrated to show the effectiveness of the Improved genetic algorithms.

• Computers and Concrete
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• 제17권4호
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• pp.435-453
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• 2016

The main purpose of this study is to perform optimum cost design of cut and cover RC shallow tunnels using Artificial bee colony and genetic algorithms. For this purpose, mathematical expressions of objective function, design variables and constraints for the design of cut and cover RC shallow tunnels were determined. By using these expressions, optimum cost design of the Trabzon Kalekapisi junction underpass tunnel was carried out by using the cited algorithms. The results obtained from the algorithms were compared with the results obtained from traditional design and remarkable saving from the cost of the tunnel was achieved.

• 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.

• 전자공학회논문지C
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• 제36C권6호
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• pp.27-36
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• 1999

본 논문에서는 입출력간의 연관관계가 트리구조로 표현되는 DTG에 의한 고속병렬다치논리회로를 설계하는 알고리즘을 제안하였다. 본 논문에서는 Nakajima 등에 의해 제안된 알고리즘의 문제점을 도출한 후, 최적화된 분할연산회로설계를 위하여 트리구조에 기초를 둔 수학적인 해석의 개념을 소개한다. 본 논문에서 제안한 알고리즘은 Nakajima 등에 의해 제안된 알고리즘으로는 설계가 가능하지 않았던 임의의 절점을 갖는 DTG에 대해서도 회로를 설계할 수 있다는 장점이 있다. Nakajima 등에 의해 제안된 알고리즘과 본 논문에서 제한한 알고리즘을 회로설계의 관점에서 비교하여 본 논문의 알고리즘이 모든 경우의 DTG에서 보다 최적화 설계를 할 수 있음을 증명하였다. 그리고 예제를 통해 본 논문에서 제안한 알고리즘의 유용성을 증명해 보였다.

• 상하수도학회지
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• 제12권1호
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• pp.70-80
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• 1998

Many algorithms to find a minimum cost design of water distribution network (WDN) have been developed during the last decades. Most of them have tried to optimize cost only while satisfying other constraining conditions. For this, a certain degree of simplification is required in their calculation process which inevitably limits the real application of the algorithms, especially, to large networks. In this paper, an optimum design method using the Genetic Algorithms (GA) is developed which is designed to increase the applicability, especially for the real world large WDN. The increased to applicability is due to the inherent characteristics of GA consisting of selection, reproduction, crossover and mutation. Just for illustration, the GA method is applied to find an optimal solution of the New York City water supply tunnel. For the calculation, the parameter of population size and generation number is fixed to 100 and the probability of crossover is 0.7, the probability of mutation is 0.01. The yielded optimal design is found to be superior to the least cost design obtained from the Linear Program method by $4.276 million.

• 수산해양교육연구
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• 제29권2호
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• pp.544-551
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• 2017

Metaheuristic algorithms are efficient techniques for a class of mathematical optimization problems without having to deeply adapt to the inherent nature of each problem. They are very useful for structural design optimization in which the cost of gradient computation can be very expensive. Among them, the characteristics of simulated annealing and genetic algorithms are briefly discussed. In Metropolis genetic algorithm, favorable features of Metropolis criterion in simulated annealing are incorporated in the reproduction operations of simple genetic algorithm. Numerical examples of structural design optimization are presented. The example structures are truss, breakwater and steel box girder bridge. From the theoretical evaluation and numerical experience, performance and applicability of metaheuristic algorithms for structural design optimization are discussed.