• 한국전자파학회논문지
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• 제30권4호
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• pp.261-269
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• 2019

본 논문은 레이돔과 같은 다층구조의 주파수 선택적 표면(frequency selective surfaces: FSS)을 설계하는데, 편파나 입사각 등 다양한 고려사항에 대한 유연성을 갖는 픽셀 형태의 주파수 선택적 표면을 설계하는 것에 관한 것이다. 픽셀 형태의 FSS를 설계할 때 이산 공간 문제를 해결할 수 있는 다양한 방법 중 이진 입자 군집 최적화(binary particle swarm optimization: BPSO) 알고리즘은 FSS의 주기구조 패턴을 결정하는데 쉽게 적용 가능한 기술 중 하나이며, 따라서 향상된 BPSO 알고리즘을 통해 롤 오프 전파 투과특성을 갖는 FSS를 효율적으로 설계하는 기법을 제안하였다. 원하는 솔루션에 입자를 유도하기 위한 적합성 함수 설계에 대하여 수렴속도 문제를 해결하기 위해, '기울기'를 입력 변수로 한 적합성 함수를 적용할 경우 쉽게 원하는 전파특성을 갖는 FSS를 얻을 수 있었다.

• Industrial Engineering and Management Systems
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• 제6권2호
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• pp.136-145
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• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권4호
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• pp.1106-1127
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• 2012

Service oriented architecture (SOA) lends itself to model the application components to coarse-grained services in such a way that the composition of different services could be feasible. Service composition fulfills numerous service requirements by constructing composite applications with various services. As it is the case in many real-world applications, different users have diverse QoS demands issuing for composite applications. In this paper, we present a service composition framework for a typical service overlay network (SON) considering both multiple QoS constraints and load balancing factors. Moreover, a service selection algorithm based on niching technique and particle swarm optimization (PSO) is proposed for the service composition problem. It supports optimization problems with multiple constraints and objective functions, whether linear or nonlinear. Simulation results show that the proposed algorithm results in an acceptable level of efficiency regarding the service composition objective under different circumstances.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.1873-1881
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• 2014

This paper deals with the design of multi-machine power system stabilizers (PSSs) and Static var compensator (SVC) using Modified shuffled frog leaping algorithm (MSFLA). The effectiveness of the proposed scheme for optimal setting of the PSSs and SVC controllers has been attended. The PSSs and SVC controllers designing is converted to an optimization problem in which the speed deviations between generators are involved. In order to compare the capability of PSS and SVC, they are designed independently once, and in a coordinated mode once again. The proposed method is applied on a multi-machine power system under different operating conditions and disturbances to confirm the effectiveness of it. The results of tuned PSS controller based on MSFLA (MSFLAPSS) and tuned SVC controller based on MSFLA (MSFLA SVC) are compared with the Strength pareto evolutionary algorithm (SPEA) and Particle swarm optimization (PSO) based optimized PSS and SVC through some performance to reveal its strong performance.

• Nuclear Engineering and Technology
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• 제55권6호
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• pp.2215-2221
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• 2023

In order to further meet the requirements of weight, volume, and dose minimization for new nuclear energy devices, the bare-bones multi-objective particle swarm optimization algorithm is used to automatically and iteratively optimize the design parameters of radiation shielding system material, thickness, and structure. The radiation shielding optimization program based on the bare-bones particle swarm optimization algorithm is developed and coupled into the reactor radiation shielding multi-objective intelligent optimization platform, and the code is verified by using the Savannah benchmark model. The material type and thickness of Savannah model were optimized by using the BBMOPSO algorithm to call the dose calculation code, the integrated optimized data showed that the weight decreased by 78.77%, the volume decreased by 23.10% and the dose rate decreased by 72.41% compared with the initial solution. The results show that the method can get the best radiation shielding solution that meets a lot of different goals. This shows that the method is both effective and feasible, and it makes up for the lack of manual optimization.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 제38회 하계학술대회
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• pp.425-426
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• 2007

In power systems operation, state estimation takes an important role in security control. For the state estimation problem, conventional optimization algorithm, such as weighted least squares (WLS) method, has been widely used. But these algorithms have disadvantages of converging local optimal solution. In these days, a modern heuristic optimization methods such as Particle Swarm Optimization (PSO), are introducing to overcome the problems of classical optimization. In this paper, we suggested parallel particle swarm optimization (PPSO) to search an optimal solution of state estimation in power systems. To show the usefulness of the proposed method over the conventional PSO, proposed method is applied on the IEEE-57 bus system.

• 정보처리학회논문지B
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• 제18B권1호
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• pp.39-44
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• 2011

본 논문에서는 최근 Xin-She Yang에 의해 소개된 반딧불이 알고리즘(FA)에 휴리스틱을 적용하여 개선하는 방안을 제안한다. 또한 이를 위하여 기존의 FA를 이와 유사한 문제영역의 알고리즘인 Particle Swarm Optimization(PSO)와 정확도 측면, 수렴 시간 측면, 각 입자의 움직임 측면에서 비교 분석한다. 비교 실험 결과, FA의 정확도는 PSO보다 나쁘지 않았지만, 수렴 속도는 느린 것으로 나타났다. 본 논문은 이에 대한 직관적인 원인을 고찰하고, 이를 극복하기 위해, 기존의 FA에 부분 돌연변이 휴리스틱을 적용하여 개선된 FA(Improved FA)를 제안한다. 벤치마크 함수들을 최적화 하는 비교 실험 결과, 개선된 FA가 PSO와 기존의 FA보다 정확도와 수렴속도 측면에서 우수함을 보이고자 한다.

• 한국통신학회논문지
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• 제35권1C호
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• pp.87-95
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• 2010

본 논문에서는 UWB (Ultra Wide Band) 시스템에서 PSO (Particle Swarm Optimization)를 사용하는 향상된 TDoA (Time Difference of Arrival) 무선측위 기법을 제안한다. 제안된 기법은 TDoA 파라미터 재추정과 태그(Tag) 위치 재측정을 수행하는 두 단계로 구성된다. 이들 두 단계에서 PSO 알고리즘은 무선측위 성능 향상을 위해 고용된다. 첫 번째 단계에서 TDoA 추정 오차를 줄이기 위해, 제안된 기법은 전형적인 TDoA 무선측위 방식으로부터 얻어진 TDoA 파라미터를 재추정한다. 두 번째 단계에서 무선측위 오차를 최소화시키기 위해, 첫 번째 단계에서 추정된 TDoA 파라미터를 가지고 제안된 기법은 태그의 위치를 다시 측정한다. 모의실험 결과, 제안된 기법은 LoS (Line-of-Sight)와 NLoS (Non-Line-of-Sight) 채널 환경에서 모두 전형적인 TDoA 무선측위 방식에 비해 우수한 무선측위 성능을 달성하는 것을 확인할 수 있었다.

• Journal of Electrical Engineering and Technology
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• 제7권4호
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• pp.501-512
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• 2012

Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.

• Structural Engineering and Mechanics
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• 제50권3호
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• pp.323-347
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• 2014

This paper proposes a Particle Swarm Optimization (PSO) algorithm, which is improved by making use of the Harmony Search (HS) approach and called HS-PSO algorithm. A computer code is developed for optimal sizing design of non-linear steel frames with various semi-rigid and rigid beam-to-column connections based on the HS-PSO algorithm. The developed code selects suitable sections for beams and columns, from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange W-shapes, such that the minimum total cost, which comprises total member plus connection costs, is obtained. Stress and displacement constraints of AISC-LRFD code together with the size constraints are imposed on the frame in the optimal design procedure. The nonlinear moment-rotation behavior of connections is modeled using the Frye-Morris polynomial model. Moreover, the P-${\Delta}$ effects of beam-column members are taken into account in the non-linear structural analysis. Three benchmark design examples with several types of connections are presented and the results are compared with those of standard PSO and of other researches as well. The comparison shows that the proposed HS-PSO algorithm performs better both than the PSO and the Big Bang-Big Crunch (BB-BC) methods.