• Structural Engineering and Mechanics
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• 제75권2호
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• pp.175-191
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• 2020

In this study, multi-story structures are actively controlled using metaheuristic algorithms. The soil conditions such as dense, normal and soft soil are considered under near-fault ground motions consisting of two types of impulsive motions called directivity effect (fault normal component) and the flint step (fault parallel component). In the active tendon-controlled structure, Proportional-Integral-Derivative (PID) type controller optimized by the proposed algorithms was used to achieve a control signal and to produce a corresponding control force. As the novelty of the study, the parameters of PID controller were determined by different metaheuristic algorithms to find the best one for seismic structures. These algorithms are flower pollination algorithm (FPA), teaching learning based optimization (TLBO) and Jaya Algorithm (JA). Furthermore, since the influence of time delay on the structural responses is an important issue for active control systems, it should be considered in the optimization process and time domain analyses. The proposed method was applied for a 15-story structural model and the feasible results were found by limiting the maximum control force for the near-fault records defined in FEMA P-695. Finally, it was determined that the active control using metaheuristic algorithms optimally reduced the structural responses and can be applied for the buildings with the soil-structure interaction (SSI).

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.147-158
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• 2022

Cloud Computing offers flexible, on demand, ubiquitous resources for cloud users. Cloud users are provided computing resources in a virtualized environment. In order to meet the growing demands for computing resources, data centres contain a large number of physical machines accommodating multiple virtual machines. However, cloud data centres cannot utilize their computing resources to their total capacity. Several policies have been proposed for improving energy proficiency and computing resource utilization in cloud data centres. Virtual machine placement is an effective method involving efficient mapping of virtual machines to physical machines. However, the availability of many physical machines accommodating multiple virtual machines in a data centre has made the virtual machine placement problem a non deterministic polynomial time hard (NP hard) problem. Metaheuristic algorithms have been widely used to solve the NP hard problems of multiple and conflicting objectives, such as the virtual machine placement problem. In this context, we presented essential concepts regarding virtual machine placement and objective functions for optimizing different parameters. This paper provides a taxonomy of metaheuristic algorithms for the virtual machine placement method. It is followed by a review of prominent research of virtual machine placement methods using meta heuristic algorithms and comparing them. Finally, this paper provides a conclusion and future research directions in virtual machine placement of cloud computing.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.979-986
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• 2002

Constraint Programming is an appealing technology for modeling and solving various real-world problems. and metaheuristic is the most successful technique available for solving large real-world vehicle routing problems. Constraint Programming and metaheuristic are complementary to each other. This paper describes how iterative improvement techniques can be used in a Constraint Programming framework(LOG Solver and ILOG Dispatcher) for Vehicle Routing Problem. As local search gets trapped in local solution, the improvement techniques are used in conjunction with metaheuristic method.

• 대한전자공학회논문지TC
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• 제46권5호
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• pp.26-35
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• 2009

OFDM (Orthogonal Frequency Division Multiplexing) 시스템은 주파수 선택적 페이딩 (frequency selective fading)과 협대역 간섭 (narrowband interference)에 강한 전송 방식으로 대용량 데이터 통신에 적합하다. 하지만 독립적으로 변조된 다수의 부반송파들이 동위상으로 중첩되면서 신호의 진폭이 증가하여 PAPR (Peak-to-Average Power Ratio)이 증가하는 문제가 발생한다. PAPR 문제를 해결하기 위해 제안된 위상회전 기법은 OFDM 신호에 위상 가중치를 곱하여 신호의 비선형 왜곡 없이 PAPR을 감소시킬 수 있지만, 위상 가중치를 탐색하는 과정에서 계산의 복잡도가 부블록 수에 따라 지수적으로 증가하는 단점이 있다. 따라서 위상회전 기법의 위상 탐색 과정에 계산의 복잡도를 감소시키면서 효율적으로 위상 가중치를 구할 수 있는 기술의 연구가 필요하다. 본 논문에서는 최적해를 구하기 위하여 사용되는 Metaheuristic 알고리즘을 위상탐색 과정에 적용하기 위한 모델링 과정을 제시하고 PTS 기법에 최적화함으로써 PAPR을 감소시키는 구조를 제안한다. 이 구조는 PTS 기법의 위상 탐색 과정에서 계산 복잡도가 지수적으로 증가하는 문제를 해결하고 PAPR 감소 성능도 보장할 수 있다. 제안하는 알고리즘을 통신 시스템에 적용하였을 때 PAPR 감소 효율을 시뮬레이션을 통해 분석했다.

• Advances in Computational Design
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• 제8권4호
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• pp.295-307
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• 2023

This paper presents an optimization of the reinforced concrete ribbed slab in terms of minimum CO₂ emissions and an economic justification of the final optimal design. The design variables are six geometry variables including the slab thickness, the ribs spacing, the rib width at the lower and toper end, the depth of the rib and the bar diameter of the reinforcement, and the seventh variable defines the concrete strength. The objective function is considered to be the minimum amount of carbon dioxide gas (CO₂) emission and at the same time, the optimal design is economical. Seven significant design constraints of American Concrete Institute's Standard were considered. A robust metaheuristic optimization method called improved dolphin echolocation and ant colony optimization (IDEACO) has been used to obtain the best possible answer. At optimal design, the three most important sources of CO₂ emissions include concrete, steel reinforcement, and formwork that the contribution of them are 63.72, 32.17, and 4.11 percent respectively. Formwork, concrete, steel reinforcement, and CO₂ are the four most important sources of cost with contributions of 67.56, 19.49, 12.44, and 0.51 percent respectively. Results obtained by IDEACO show that cost and CO₂ emissions are closely related, so the presented method is a practical solution that was able to reduce the cost and CO₂ emissions simultaneously.

• 디지털융복합연구
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• 제12권5호
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• pp.125-130
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• 2014

오늘날의 글로벌 시장에서의 경쟁은 많은 회사들이 시장에서 충분한 다양성을 가진 product family를 개발하도록 하고 있다. Product family를 설계할 때 중요한 이슈 중에 하나는 제품의 공통성과 차별성간의 절충점을 찾아내는 것이다, 이와 동시에 Product family를 설계할 때 리드타임을 단축시키고, 품질을 향상시키며 비용을 절감하는 것뿐만 아니라 제품의 환경 성능을 고려하는 것도 필요하다. 본 연구에서는 환경성을 고려한 메타 휴리스틱 알고리즘 기반의 그린 Product Family 재설계 방법론을 제안한다. 제안하는 방법은 그린 product family의 설계를 위해 메타휴리스틱 알고리즘으로써 유전자 알고리즘과 green product family index (GPFI)를 이용한다. 추가적으로 product family 레벨과 부품 레벨의 product family 재설계 추천방안도 제시하였다. 본 연구에서는 테이블 램프 product family를 대상으로 제안한 방법의 효율성과 타당성을 검증하였다.

• Journal of electromagnetic engineering and science
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• 제19권1호
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• pp.31-36
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• 2019

In this study, an effective method for designing an electromagnetic multilayer radome is introduced. This method is achieved by using ant colony optimization for a continuous domain in the transmission coefficient maximization with stability for a wide angle of incidence in both perpendicular and parallel polarizations in specific X- and Ku-bands. To obtain the optimized parameter for a C-sandwich radome, particle swarm optimization algorithm is operated to give a clear comparison on the effectiveness of ant colony optimization for a continuous domain. The qualification of an optimized multilayer radome is also compared with an effective solid radome type in transmitted power stability and presented in this research.

• Journal of Advanced Marine Engineering and Technology
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• 제40권2호
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• pp.138-145
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• 2016

This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

• Structural Engineering and Mechanics
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• 제45권5호
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• pp.643-654
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• 2013

Optimum cost design of columns subjected to axial force and uniaxial bending moment is presented in this paper. In the formulation of the optimum design problem, the height and width of the column, diameter and number of reinforcement bars are treated as design variables. The design constraints are implemented according to ACI 318-08 and studies in the literature. The objective function is taken as the cost of unit length of the column consisting the cost of concrete, steel, and shuttering. The solution of the design problem is obtained using the artificial bee colony algorithm which is one of the recent additions to metaheuristic techniques. The Artificial Bee Colony Algorithm is imitated the foraging behaviors of bee swarms. In application of this algorithm to the constraint problem, Deb's constraint handling method is used. Obtained results showed that the optimum value of numerical example is nearly same with the existing values in the literature.

• Journal of Advanced Marine Engineering and Technology
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• 제38권10호
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• pp.1340-1346
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• 2014

Previous studies of reliable server assignment considered only to assign the same cost of server, that is, homogeneous servers. In this paper, we generally deal with reliable server assignment with different server costs, i.e., heterogeneous servers. We formulate this problem as a nonlinear integer programming mathematically. Our problem is defined as determining a deployment of heterogeneous servers to maximize a measure of service availability. We propose two metaheuristic algorithms (tabu search and particle swarm optimization) for solving the problem of reliable server assignment. From the computational results, we notice that our tabu search outstandingly outperforms particle swarm optimization for all test problems. In terms of solution quality and computing time, the proposed method is recommended as a promising metaheuristic for a kind of reliability optimization problems including reliable sever assignment and e-Navigation system.