• 한국소음진동공학회논문집
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• 제15권11호
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• pp.1223-1231
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• 2005

Recently, the issue of ship nitration due to the large scale, high speed and lightweight of ship is emerging. For pleasantness in the cabin, shipbuilders are asked for strict vibration criteria and the degree of nitration level at a deckhouse became an important condition for taking order from customers. This study proposes a new optimization framework that is NASTRAN external call type optimization method (OptShip) and applies to an optimum design to decrease the nitration level of a deckhouse. The merits of this method are capable of using of global searching method and selecting of various objective function and design variables. The global optimization algorithms used here are random tabu search method which has fast converging speed and searches various size domains and genetic algorithm which searches multi-point solutions and has a good search capability in a complex space. By adapting OptShip to full-scale model, the validity of the suggested method was investigated.

• 산업경영시스템학회지
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• 제42권3호
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• pp.1-7
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• 2019

It is one of the known methods to obtain the optimal solution using the Ant Colony Optimization Algorithm for the Traveling Salesman Problem (TSP), which is a combination optimization problem. In this paper, we solve the TSP problem by proposing an improved new ant colony optimization algorithm that combines genetic algorithm mutations in existing ant colony optimization algorithms to solve TSP problems in many cities. The new ant colony optimization algorithm provides the opportunity to move easily fall on the issue of developing local optimum values of the existing ant colony optimization algorithm to global optimum value through a new path through mutation. The new path will update the pheromone through an ant colony optimization algorithm. The renewed new pheromone serves to derive the global optimal value from what could have fallen to the local optimal value. Experimental results show that the existing algorithms and the new algorithms are superior to those of existing algorithms in the search for optimum values of newly improved algorithms.

• Structural Engineering and Mechanics
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• 제81권6호
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• pp.677-689
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• 2022

Generally, the goal of seismic retrofit design of an existing structure using energy dissipation devices is to determine the optimum design parameters of a retrofit device to satisfy a specified limit state with minimum cost. However, the presence of multiple parameters to be optimized and the computational complexity of performing non-linear analysis make it difficult to find the optimal design parameters in the realistic 3D structure. In this study, genetic algorithm-based optimal seismic retrofit methods for determining the required number, yield strength, and location of steel slit dampers are proposed to retrofit an asymmetric soft first-story structure. These methods use a multi-objective and single-objective evolutionary algorithms, each of which varies in computational complexity and incorporates nonlinear time-history analysis to determine seismic performance. Pareto-optimal solutions of the multi-objective optimization are found using a non-dominated sorting genetic algorithm (NSGA-II). It is demonstrated that the developed multi-objective optimization methods can determine the optimum number, yield strength, and location of dampers that satisfy the given limit state of a three-dimensional asymmetric soft first-story structure. It is also shown that the single-objective distribution method based on minimizing plan-wise stiffness eccentricity turns out to produce similar number of dampers in optimum locations without time consuming nonlinear dynamic analysis.

• 융합신호처리학회논문지
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• 제13권4호
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• pp.207-210
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• 2012

유전 알고리즘은 확률에 기반한 매우 효과적인 최적화 기법이지만 지역해로의 조기수렴과 전역해로의 수렴 속도가 느리다는 단점이 있다. 본 논문에서는 이러한 단점을 보완하기 위해 적응 분할법에 기반한 유전 알고리즘을 제안하였다. 유전 알고리즘이 전역해를 효과적으로 찾도록 하는 적응 분할법은 최적화의 복잡도를 줄이기 위해 탐색공간을 적응적으로 분할한다. 이러한 적응 분할법은 탐색공간의 복잡도가 증가할수록 더 효과적이다. 제안된 방법을 테스트 함수의 최적화 및 도립진자 제어를 위한 퍼지 제어기 설계 최적화에 적용하여 그 유효성을 보였다.

• 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.

• 한국전산구조공학회논문집
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• 제21권1호
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• pp.21-34
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• 2008

이 논문에서는 철근콘크리트 프레임 구조물을 대상으로 직접탐색기법을 도입하여 보다 개선된 유전자 알고리즘을 이용한 최적설계 기법을 제안하고 있다. 먼저 유전자 알고리즘을 이용하여 다양한 초기 가정 단면을 발생시키고, 이로부터 도출되는 각 설계 부재력 조건에 대해 미리 구성한 설계 단면 데이터베이스(DB)를 기반으로 회귀분석과 직접탐색을 이용하여 최적해를 도출한 후 여러 세대에 걸쳐 누적된 결과로부터 전역 최적해(global minimum)를 선택하였다. 제안된 알고리즘은 일반적인 유전자 알고리즘만을 이용할 경우 전역 최적해에 도달하기까지 수렴성이 떨어져서 그 결과 해의 적합도(Fitness)가 저하되는 단점을 보완하여 빠른 수렴성과 함께 최종해의 경제성에서도 향상된 결과를 보인다. 또한, 작용 하중 조건 하에서 전 부재가 최대의 효율로 저항함으로써 보다 경제적인 설계가 되도록 하기 위하여 비선형 해석을 수행하여 도출된 부재력을 바탕으로 설계 단면을 결정하였으며, 제안된 알고리즘을 예제 구조물에 적용하여 그 효율성을 검증하였다.

• 한국농공학회논문집
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• 제62권6호
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• pp.51-62
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• 2020

The objective of this study was to estimate an optimum ecological flow rate in the Banbyeon stream based on the two representative fish species. Hydraulic stream environment was simulated with HEC-RAS for two water flow regimes and used for the PHABSIM hydraulic simulation. A dominant species of Zacco platypus and an endemic species of Squalidus chankaensis tsuchigae were selected as the representative fishes whose habitat conditions were evaluated for the spawning and adult stages. Weighted usable area (WUA) was estimated based on habitat suitability index (HSI) and PHABSIM habitat simulation. Overall deep water zone in the stream demonstrated greater WUA which implies better habitat status. The estimated WUA for Zacco platypus as the dominant species was about five times greater than Squalidus chankaensis tsuchigae at the stream flow of 12 ㎥/s. The optimum ecological flow rates were 15 ㎥/s and 25 ㎥/s for the respective spawning and adult stages of Zacco platypus, while 5 ㎥/s was estimated for both the life cycles of Squalidus chankaensis tsuchigae. Assuming that the dominant species may survive better in wider flow regimes, the optimum ecological flow rate should be determined rater based on the endemic species and flow rate of 5 ㎥/s was suggested for the Banbyeon stream.

• 산업경영시스템학회지
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• 제40권2호
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• pp.92-98
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• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.

• 한국해양공학회지
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• 제23권1호
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• pp.1-6
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• 2009

The paper describes results of a sensitivity study on an optimum mooring cost as a function of safety factor and allowable maximum offset of the offshore floating structure by finding the anchor leg component size and the declination angle. A harmony search (HS) based mooring optimization program was developed to conduct the study. This mooring optimization model was integrated with a frequency-domain global motion analysis program to assess both cost and design constraints of the mooring system. To find a trend of anchor leg system cost for the proposed sensitivity study, optimum costs after a certain number of improvisation were found and compared. For a case study a turret-moored FPSO with 3 ${\times}$ 3 anchor leg system was considered. To better guide search for the optimum cost, three different penalty functions were applied. The results show that the presented HS-based cost-optimum offshore mooring design tool can be used to find optimum mooring design values such as declination angle and horizontal end point separation as well as a cost-optimum mooring system in case either the allowable maximum offset or factor of safety varies.

• 한국공간구조학회논문집
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• 제12권4호
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• pp.47-56
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• 2012

This paper describes the structural design and optimization of sinusoidally corrugated web girder by using EUROCODE (EN 1993-1-5). The optimum design methodology and characteristics of the optimal cross-section are discussed. We investigate a shear buckling and the concerned standards for corrugated web and explain the equations to obtain a critical stress according to buckling type. In order to perform optimization, we consider an objective function as minimum weight of the girder and use the constraint functions as slenderness ratio and stresses of flanges as well as corrugated web and deflection. Genetic Algorithm is adopted to search a global optimum solution for this mathematical model. For numerical example, the clamped girder under the concentrated load is considered, while the optimum cross-sectional area and design variables are analyzed. From the results of the adopted example, the optimum design program of the sinusoidally corrugated web girder is able to find the suitable solution which satisfied a condition subject to constraint functions. The optimum design shows the tendency to decrease the cross-sectional area with the yielding strength increase and increase the areas with load increase. Moreover, the corrugated web thickness shows a stable increase concerning the load.