• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1999년도 봄 학술발표회 논문집
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• pp.102-109
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• 1999

Two phase simulated annealing algorithm is presented as a structural optimization technique and applied to minimum weight design of space trusses subjected to stress and displacement constraints under multiple loading conditions. Univariate searching algorithm is adopted for automatic selection of initial values of design variables for SA algorithm. The proper values of cooling factors and reasonable stopping criteria for optimum design of space truss structures are proposed to enhance the performance of optimization process. Optimum weights and design solutions are presented for two well-blown example structures and compared with those reported in the literature.

• 산업기술연구
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• 제22권A호
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• pp.19-28
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• 2002

The Nelder-Mead simplex algorithm has been one of the most widely used methods for the nonlinear unconstrained optimization, since 1965. Recently, the new algorithm, (so-called the Fuzzy Simplex Algorithm), with fuzzy logic controllers for the expansion, reflection and contraction process of this algorithm has been proposed. In this paper, this new algorithm is developed. And, the formulation for the optimum design of the power screw's efficiency is made. And then, the developed fuzzy simplex algorithm as well as the original one is applied to this optimum design problem. The Fuzzy simplex algorithm results in a faster convergence in this problem, as reported in other study, too.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2002년도 추계학술대회논문집
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• pp.1034-1037
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• 2002

This paper presents an optimum design of rotor-bearing system using a hybrid method to compute the solutions of optimization problem. The present hybrid algorithm namely Enhanced Artificial Life Algorithm(EALA), is a synthesis of an artificial life algorithm(ALA) and the random tabu search(R-tabu) method. We applied EALA to the optimum design of rotor-shaft system supported by the floating ring journal bearings. we will propose the optimum shape of rotor, position and shape of bearings. Through this study, we investigate the reliability and usefulness of EALA.

• 전자공학회논문지B
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• 제31B권7호
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• pp.49-57
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• 1994

An efficient approach for the computationtion of the optimum convergence factor is proposed for the LMS algorithm applied to a transversal FIR structure in this study. The approach automatically leads to an optimum step size algorithm at each weight in every iteration that results in a dramatic reduction in terms of convergence time. The algorithm is evaluated in system identification application where two alternative computer simulations are considered for time-invariant and time-varying system cases. The results show that the proposed algorithm needs not appropriate convergence factor and has better performance than AGC(Automatic Gain Control) algorithm and Karni algorithm, which require the convergence factors controlled arbitrarily in computer simulation for time-invariant system and time-varying systems. Also, itis shown that the proposed algorithm has the excellent adaptability campared with NLMS(Normalized LMS) algorithm and RLS (Recursive least Square) algorithm for time-varying circumstances.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.533-538
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• 2001

This paper describes a combinational method to compute the global and local solutions of optimization problems. The present hybrid algorithm uses both a genetic algorithm and a local concentrate search algorithm (e. g simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm but also supplies a more accurate solution. In addition, this algorithm can find the global and local optimum solutions. The present algorithm can be supplied to minimize the resonance response (Q factor) and to yield the critical speeds as far from the operating speed as possible. These factors play very important roles in designing a rotor-bearing system under the dynamic behavior constraint. In the present work, the shaft diameter, the bearing length, and clearance are used as the design variables.

• Structural Engineering and Mechanics
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• 제52권2호
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• pp.351-368
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• 2014

This study presents a hunting search based optimum design algorithm for engineering optimization problems. Hunting search algorithm is an optimum design method inspired by group hunting of animals such as wolves, lions, and dolphins. Each of these hunters employs hunting in a different way. However, they are common in that all of them search for a prey in a group. Hunters encircle the prey and the ring of siege is tightened gradually until it is caught. Hunting search algorithm is employed for the automation of optimum design process, during which the design variables are selected for the minimum objective function value controlled by the design restrictions. Three different examples, namely welded beam, cellular beam and moment resisting steel frame are selected as numerical design problems and solved for the optimum solution. Each example differs in the following ways: Unlike welded beam design problem having continuous design variables, steel frame and cellular beam design problems include discrete design variables. Moreover, while the cellular beam is designed under the provisions of BS 5960, LRFD-AISC (Load and Resistant Factor Design-American Institute of Steel Construction) is considered for the formulation of moment resisting steel frame. Levy Flights is adapted to the simple hunting search algorithm for better search. For comparison, same design examples are also solved by using some other well-known search methods in the literature. Results reveal that hunting search shows good performance in finding optimum solutions for each design problem.

• 전자공학회논문지A
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• 제33A권5호
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• pp.1-9
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• 1996

In this paper, we propose an efficient computational algorithm that can reduce significantly the computational complexity of the ML optimum multiuser detector known as the most excellent detector in synchronous code division multiple access channels. The proposed detector uses the sequential detection algorithm based on the alternating maximization appraoch to obtain the ML estimates. As initial estimates for this sequential algorithm, we can use the estimated values obtained by the conventional single-user detector, the linear decorrelating multiuser detector, or the decorrelating decision-feedback muliuser detector, the linear decorrelating multiuser detector, or the decorrelating decision-feedback multiuser detector. We have performed computer simulations in order to see the convergence behaviors and the detection performance of the propsoed algorithm in terms of initial algorithms and the number of users, and then to compare the computational complexity with that of the ML optimum multiuser detector. From the results, we have seen that the proposed alternating maximization detector has nearly equal detction performance with that of the ML optimum multiuser detctor in only a few iteration.

• 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.

• 한국통신학회논문지
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• 제17권8호
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• pp.846-855
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• 1992

In this paper, the decrease multipoint search method and Its learning algorithm for optimum value computatlon method of object function Is proposed. Using this method, the number of evaluation point according to searching time can t)e reduced multipoint of the direct search method by applying the unlivarlate method. And the learning algorithm can reprat the same search method in a new established boundary by using the searched result. In order to Investigate the efficience of algorithm, this method this method is applied to Rosenbrock and Powell, Colvelle function that are Impossible or uncertain in traditional direct search method. And the result of application, the optimum value searching oil every function Is successful. Especially, the algorithm is certified as a good calculation method for producing global(absolute) optimum value.

• Computers and Concrete
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• 제10권3호
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• pp.295-306
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• 2012

Optimum cost design of a simply supported reinforced concrete beam is presented in this paper. In the formulation of the optimum design problem, the height and width of the beam, and reinforcement steel area 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 beam 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.