• 한국지능시스템학회논문지
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• 제15권6호
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• pp.730-735
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• 2005

배낭 문제는 단순한 것 같지만 조합 최적화 문제로서, 다항 시간(polynomial time)에 풀리지 않는 NP-hard 문제이다. 이 문제를 해결하기 위해 기존에는 GA(Genetic Algorithms)를 이용하여 해결하였다. 하지만 기존의 방법은 DNA의 정확한 특성을 고려하지 않아, 실제 실험과의 결과 차이가 발생하고 있다. 본 논문에서는 배낭 문제의 문제점을 해결하기 위해 DNA 컴퓨팅 기법에 DNA 코딩 방법을 적용한 ACO(Algorithm for Code Optimization)를 제안한다. ACO는 배낭 문제 중 (0,1)-배낭 문제에 적용하였고, 그 결과 기존의 방법보다 실험적 오류를 최소화하였으며, 또한 적합한 해를 빠른 시간내에 찾을 수 있었다.

• 한국세라믹학회지
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• 제48권6호
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• pp.493-498
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• 2011

Optimal atomic configurations in a nanoparticle were predicted by genetic algorithm. A truncated octahedron with a fixed composition of 1 : 1 was investigated as a model system. A Python code for genetic algorithm linked with a molecular dynamics method was developed. Various operators were implemented to accelerate the optimization of atomic configuration for a given composition and a given morphology of a nanoparticle. The combination of random mix as a crossover operator and total_inversion as a mutation operator showed the most stable structure within the shortest calculation time. Pt-Ag core-shell structure was predicted as the most stable structure for a nanoparticle of approximately 4 nm in diameter. The calculation results in this study led to successful prediction of the atomic configuration of nanoparticle, the size of which is comparable to that of practical nanoparticls for the application to the nanocatalyst.

• 대한전기학회논문지:전력기술부문A
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• 제48권4호
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• pp.388-394
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• 1999

This paper is concerned with an application of Parallel Genetic Algorithms(PGA) to optimal econmic load dispatch(ELD) in power systems. The ELD problem is to minimize the total generation fuel cost of power outputs for all generating units while satisfying load balancing constraints. Genetic Algorithms(GA) is a good candidate for effective parallelization because of their inherent principle of evolving in parallel a population of individuals. Each individual of a population evaluates the fitness function without data exchanges between individuals. In application of the parallel processing to GA, it is possible to use Single Instruction stream, Multiple Data stream(SIMD), a kind of parallel system. The architecture of SIMD system need not data communications between processors assigned. The proposed ELD problem with C code is implemented by SIMSCRIPT language for parallel processing which is a powerfrul, free-from and versatile computer simulation programming language. The proposed algorithms has been tested for 38 units system and has been compared with Sequential Quadratic programming(SQP).

• Structural Engineering and Mechanics
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• 제86권3호
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• pp.337-348
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• 2023

The optimization of reinforced concrete (RC) cantilever retaining walls is a complex problem and requires the use of advanced techniques like metaheuristic algorithms. For this purpose, an optimization model must first be developed, which involves mathematical complications, multidisciplinary knowledge, and programming skills. This task has proven to be too arduous and has halted the mainstream acceptance of optimization. Therefore, it is necessary to unravel the complications of optimization into an easily applicable form. Currently, the most commonly used method for designing retaining walls is by following the proportioning limits provided by the ACI handbook. However, these limits, derived manually, are not verified by any optimization technique. There is a need to validate or modify these limits, using optimization algorithms to consider them as optimal limits. Therefore, this study aims to propose updated proportioning limits for the economical design of a RC cantilever retaining wall through a comprehensive parametric investigation using the genetic algorithm (GA). Multiple simulations are run to examine various design parameters, and trends are drawn to determine effective ranges. The optimal limits are derived for 5 geometric and 3 reinforcement variables and validated by comparison with their predecessor, ACI's preliminary proportioning limits. The results indicate close proximity between the optimized and code-provided ranges; however, the use of optimal limits can lead to additional cost optimization. Modifications to achieve further optimization are also discussed. Besides the geometric variables, other design parameters not covered by the ACI building code, like reinforcement ratios, bar diameters, and material strengths, and their effects on cost optimization, are also discussed. The findings of this investigation can be used by experienced engineers to refine their designs, without delving into the complexities of optimization.

• 한국컴퓨터정보학회논문지
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• 제21권12호
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• pp.1-10
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• 2016

In this paper, we attempt to prevent certain cases by tracing a history and making genogram about open source software and its modification using similarity of source code. There are many areas which use open source software actively and widely, and open source software contributes their development. However, there are many unconscious cases like ignoring license or intellectual properties infringe which can lead litigation. To prevent such situation, we analyze source code similarity using program dependence graph which resembles subgraph isomorphism problem, a typical NP-complete problem. To solve subgraph isomorphism problem, we utilized harmony search of metaheuristic algorithm and compared its result with a genetic algorithm. For the future works, we represent open source software as program dependence graph and analyze their similarity.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2008년도 춘계학술대회논문집
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• pp.377-380
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• 2008

In this study, an aerodynamic shape optimization system was developed to study the optimal shape of airfoil. The system consists of GA (Genetic Algorithm) and CFD code based on the Navier-Stokes equation. Lift-drag ratio is chosen as the object function and optimization is conducted for PARSEC airfoil with nine design variables, which is very efficient in representing the surface geometry of airfoil.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 1997년도 추계학술대회 발표논문집:21세기를 향한 정보통신 기술의 전망
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• pp.63-77
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• 1997

유전자 알고리즘(Genetic Algorithms)은 우수형질이 계속 번식하고 열성형질은 도태하는 자연의 진화 메커니즘을 모방한 탐색 알고리즘으로 전형적인 조합 최적화 문제에 많이 적용되고 있다. 유전자 알고리즘의 성능을 향상시키기 위해 알고리즘 실행과정에 적용할 수많은 이론과 경험적인 유전자 조작 기법이 제시되고 있는데, 이러한 기법들은 대부분 우수형질을 확보함으로써 최적의 값을 효과적으로 탐색하기 위한 것이다. 그러나, 적절하지 못한 유전자 조작의 경우 탐색지점의 제한등으로 인한 Local Optimum에 빠질 위험이 있으므로, 유전자 조작에 대한 평가가 이루어져야 한다. 본 연구에서는 유전자 알고리즘의 유전자 조작기법중 적응도 비례전략을 개선한 유전자조작이 적절한 선택기법들로 유전자 알고리즘에 응용될수 있는지를 밝히기 위해, 냅색문제를 대상으로 세대수의 변화에 따른 탐색 결과를 평가하였다.

• 전자공학회논문지C
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• 제35C권3호
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• pp.46-58
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• 1998

Multi-disk data allocation problem examined in this paper is to find a method to distribute a Binary Cartesian Product File on multiple disks to maximize parallel disk I/O accesses for partial match retrieval. This problem is known to be NP-hard, and heuristkc approaches have been applied to obtain sub-optimal solutions. Recently, efficient methods have been proposed with a restriction that the number of disks in which files are stored should be power of 2. In this paper, we propose a new disk Allocation method based on Genetic Algorithm(GA) to remove the restriction on the number of disks to be applied. Using the schema theory, we prove that our method can find a near-optimal solutionwith high probability. We compare the quality of solution derived by our method with General Disk Modulo, Binary Disk Modulo, and Error Correcting Code methods through the simulation. The simulation results show that proposed GA is superior to GDM method in all cases and provides comparable performance to the BDM method which has a restriction on the number of disks.

• Structural Engineering and Mechanics
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• 제71권5호
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• pp.503-513
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• 2019

Genetic Algorithms (GAs) have found the best design for reinforced concrete frames. The design of the optimum beam sections by GAs has been unified. The process of the optimum-design sections has satisfied axial, flexural, shear and torsion necessities based on the designing code. The frames' function has contained the function of both concrete and reinforced steel besides the function of the frames' formwork. The results have revealed that limiting the dimension of frame-beam with the dimension of frame-column have increased the optimum function of the structure, thereby reducing the reanalysis requirement for checking the optimum-designed structures through GAs.

• Journal of Information Processing Systems
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• 제18권6호
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• pp.763-769
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• 2022

Transportation allocation requires information such as storage location and order information. In order to guarantee the safe transmission and real-time sharing of information in all links, an intelligent transportation control system based on blockchain technology is designed. Firstly, the technical architecture of intelligent transportation information traceability blockchain and the overall architecture of intelligent transportation control system were designed. Secondly, the transportation management demand module and storage demand management module were designed, and the control process of each module was given. Then, the type of intelligent transportation vehicle was defined, the objective function of intelligent transportation control was designed, and the objective function of intelligent transportation control was constructed. Finally, the intelligent transportation control was realized by genetic algorithm. It was found that when the transportation order volume was 50×103, and the CPU occupancy of the designed system was only 11.8%. The reliability attenuation of the code deletion scheme was lower, indicating better performance of the designed system.