• 조명전기설비학회논문지
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• 제28권8호
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• pp.47-53
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• 2014

This paper presents an Differential Search(DS) Algorithm for solving the economic load dispatch(ELD) problems with Valve-Point loading constraints. DS algorithm simulates the Brownian-like random-walk movement used by an organism to migrate. Numerical results on a test system consisting of 13 units show that the proposed approach is faster, more robust and powerful than conventional algorithms. Case studies show the simulation results are better than Lagrange method, the Hopfield neural networks and GA.

• Smart Structures and Systems
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• 제26권3호
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• pp.345-360
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• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• 정보보호학회논문지
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• 제26권6호
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• pp.1421-1430
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• 2016

본 논문에서 우리는 ARX 구조를 가지는 블록 암호에 대한 차분 경로 탐색을 효율적으로 수행하는 방법에 대해 제안한다. 우리는 두 가지 기법을 이용하여 A. Biryukov 등이 제안한 차분 경로 자동 탐색하는 알고리즘을 최적화하였고, 이를 블록 암호 SPECK에 적용하여 Birykov의 결과보다 2~3배 향상된 결과를 얻었다. 이는 ARX 구조를 가지는 블록 암호에 대한 기제안된 결과보다 더 좋은 차분 경로를 찾는데 도움을 줄 수 있다.

• 한국콘텐츠학회논문지
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• 제20권11호
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• pp.636-643
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• 2020

차분 진화 알고리즘은 연속적인 문제 공간인 실수 최적화 문제를 해결하기 위해 개발된 메타휴리스틱 기법 중에 하나이다. 본 연구에서는 차분 진화 알고리즘을 불연속적인 문제 공간인 외판원 문제 해결에 사용하기 위하여 차분 진화 알고리즘에 난수 키 표현법을 적용하였다. 차분 진화 알고리즘은 실수 공간을 탐색하고 오름 차순으로 정렬된 해의 인덱스의 순서를 도시 방문 순서로 하여 적합도를 구한다. TSPLIB에서 제공하는 표준 외판원 문제에 적용하여 실험한 결과 제안한 난수 키 표현법 기반 차분 진화 알고리즘이 외판원 문제 해결에 가능성을 가지고 있음을 확인하였다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.549-550
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• 2021

본 논문에서는 다양한 돌연변이 전략을 인식하기 위해 MUDE (Uniform Local Search)를 사용한 다중 인구 차등 진화 알고리즘을 제안한다. MUDE에서 집단은 진화 비율(DE/rand/1 및 DE/current-to-rand/1)에 따라 서로 다른 돌연변이 전략을 수행하는 다른 집단 크기를 가진 여러 하위 집단으로 나뉜다. 인구의 다양성을 개선하기 위해 정보는 소프트 아일랜드 모델에 의해 하위 인구 간에 마이그레이션된다.

• 인터넷정보학회논문지
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• 제21권3호
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• pp.21-28
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• 2020

Fireworks Algorithm (FWA) is a relatively novel swarm-based metaheuristic algorithm for global optimization. To solve the low-efficient local searching problem and convergence of the FWA, this paper presents a Variable Amplitude Coefficient Fireworks Algorithm with Uniform Local Search Operator (namely VACUFWA). Firstly, the explosive amplitude is used to adjust improving the convergence speed dynamically. Secondly, Uniform Local Search (ULS) enhances exploitation capability of the FWA. Finally, the ULS and Variable Amplitude Coefficient operator are used in the VACUFWA. The comprehensive experiment carried out on 13 benchmark functions. Its results indicate that the performance of VACUFWA is significantly improved compared with the FWA, Differential Evolution, and Particle Swarm Optimization.

• ETRI Journal
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• 제45권1호
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• pp.119-130
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• 2023

We propose a quantized gradient search algorithm that can achieve global optimization by monotonically reducing the quantization step with respect to time when quantization is composed of integer or fixed-point fractional values applied to an optimization algorithm. According to the white noise hypothesis states, a quantization step is sufficiently small and the quantization is well defined, the round-off error caused by quantization can be regarded as a random variable with identically independent distribution. Thus, we rewrite the searching equation based on a gradient descent as a stochastic differential equation and obtain the monotonically decreasing rate of the quantization step, enabling the global optimization by stochastic analysis for deriving an objective function. Consequently, when the search equation is quantized by a monotonically decreasing quantization step, which suitably reduces the round-off error, we can derive the searching algorithm evolving from an optimization algorithm. Numerical simulations indicate that due to the property of quantization-based global optimization, the proposed algorithm shows better optimization performance on a search space to each iteration than the conventional algorithm with a higher success rate and fewer iterations.

• Advances in Computational Design
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• 제1권1호
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• pp.79-86
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• 2016

In this study, the three different meta-heuristics namely the Grey Wolf Optimizer (GWO), Stochastic Fractal Search (SFS), and Adaptive Differential Evolution with Optional External Archive (JADE) algorithms are examined. This study considers optimization of the planer frame to minimize its weight subjected to the strength and displacement constraints as per the American Institute of Steel and Construction - Load and Resistance Factor Design (AISC-LRFD). The GWO algorithm is associated with grey wolves' activities in the social hierarchy. The SFS algorithm works on the natural phenomenon of growth. JADE on the other hand is a powerful self-adaptive version of a differential evolution algorithm. A one-bay ten-story planar steel frame problem is examined in the present work to investigate the design ability of the proposed algorithms. The frame design is produced by optimizing the W-shaped cross sections of beam and column members as per AISC-LRFD standard steel sections. The results of the algorithms are compared. In addition, these results are also mapped with other state-of-art algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권10호
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• pp.3815-3833
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• 2021

MILP-based automatic search is the most common method in analyzing the security of cryptographic algorithms. However, this method brings many issues such as low efficiency due to the large size of the model, and the difficulty in finding the contradiction of the impossible differential distinguisher. To analyze the security of ESF algorithm, this paper introduces a simplified MILP-based search model of the differential distinguisher by reducing constrains of XOR and S-box operations, and variables by combining cyclic shift with its adjacent operations. Also, a new method to find contradictions of the impossible differential distinguisher is proposed by introducing temporary variables, which can avoid wrong and miss selection of contradictions. Based on a 9-round impossible differential distinguisher, 15-round attack of ESF can be achieved by extending forward and backward 3-round in single-key setting. Compared with existing results, the exact lower bound of differential active S-boxes in single-key setting for 10-round ESF are improved. Also, 2108 9-round impossible differential distinguishers in single-key setting and 14 12-round impossible differential distinguishers in related-key setting are obtained. Especially, the round of the discovered impossible differential distinguisher in related-key setting is the highest, and compared with the previous results, this attack achieves the highest round number in single-key setting.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.123-133
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• 2023

Active queue management (AQM) is a leading congestion control system, which can keep smaller queuing delay, less packet loss with better network utilization and throughput by intentionally dropping the packets at the intermediate hubs in TCP/IP (transmission control protocol/Internet protocol) networks. To accelerate the responsiveness of AQM framework, proportional-integral-differential (PID) controllers are utilized. In spite of its simplicity, it can effectively take care of a range of complex problems; however it is a lot complicated to track down optimal PID parameters with conventional procedures. A few new strategies have been grown as of late to adjust the PID controller parameters. Therefore, in this paper, we have developed a Squirrel search based PID controller to dynamically find its controller gain parameters for AQM. The controller gain parameters are decided based on minimizing the integrated-absolute error (IAE) in order to ensure less packet loss, high link utilization and a stable queue length in favor of TCP networks.