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분산형 입자군집최적화 기법을 이용한 트러스 구조물 최적 설계에 관한 연구
백현욱(Hyunwook Beak),김태형(Tea-Hyoung Kim) 대한기계학회 2012 대한기계학회 춘추학술대회 Vol.2012 No.11
This paper presents a simple and effective mechanism to handle constraints structure optimization problems based on a particle swarm optimization (PSO) algorithm. For this purpose, a novel PSO algorithm improving the searching ability by introducing the concepts of neighborhood and the mechanism inspired by quantum characteristic is first developed. This method makes the exploration ability of particles better and thus reduces the probability of premature convergence to local optima compared to conventional PSOs. Second, a simple constraints handling technique using a virtual objective function is adopted. This method does not use any additional problem-dependent variables such as Lagrangian multiplier and penalty function factor, which should be determined by user. At last, various examples of truss optimization with fixed geometries are presented to demonstrate the effectiveness and reliability of proposed PSO.
분산형 입자군집최적화 기법을 이용한 열전도 역문제의 해석에 관한 연구
백현욱(Hyunwook Beak),이영일(Youngil Lee),정정열(Jung-Yeul Jung),김태형(Tea-Hyoung Kim) 대한기계학회 2011 대한기계학회 춘추학술대회 Vol.2011 No.10
In this paper, we study on a meta-heuristic optimization methodology for the estimation of unknown heat source function in inverse heat conduction problems. Physical inverse heat conduction problem usually leads to the formulation of large-scale ill-posed nonlinear optimization problems. In order to solve such problems, a novel meta-heuristic optimization method, DPSO-QI (distributed particle swarm optimization with quantum infusion), is developed. Furthermore, Tikhonov regularization method is introduced to obtain a stabilized solution in this kind of inverse problems. Some numerical simulations are carried out to demonstrate its effectiveness, which clearly shows that the proposed DPSO-QI scheme is a novel and powerful one to estimate an unknown heat source function in inverse heat conduction problems.