• Steel and Composite Structures
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• v.45 no.4
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• pp.579-590
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• 2022

One of the biggest problems in structural steel calculation is the design of structures using the lowest possible material weight, making this a slow and costly process. To achieve this objective, several optimization methods have been developed and tested. Nevertheless, a method that performs very efficiently when applied to different problems is not yet available. Based on this assumption, this work proposes a hybrid metaheuristic algorithm for geometric and dimensional optimization of space trusses, called Simulated Squirrel Search Algorithm, which consists of an association of the well-established neighborhood shifting algorithm (Simulated Annealing) with a recently developed promising population algorithm (Squirrel Search Algorithm, or SSA). In this study, two models are tried, being respectively, a classical model from the literature (25-bar space truss) and a roof system composed of space trusses. The structures are subjected to resistance and displacement constraints. A penalty function using Fuzzy Logic (FL) is investigated. Comparative analyses are performed between the Squirrel Search Algorithm (SSSA) and other optimization methods present in the literature. The results obtained indicate that the proposed method can be competitive with other heuristics.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.89-104
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• 2008

Growth curves including Bass, Logistic and Gompertz functions are widely used in forecasting the market demand. Nonlinear least square method is often adopted for estimating the model parameters but it is difficult to set up the starting value for each parameter. If a wrong starting point is selected, the result may lead to erroneous forecasts. This paper proposes a method of selecting starting values for model parameters in estimating some growth curves by nonlinear least square method through grid search and transformation into linear regression model. Resealing the market data using the national economic index makes it possible to figure out the range of parameters and to utilize the grid search method. Application to some real data is also included, where the performance of our method is demonstrated.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.3 s.96
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• pp.346-353
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• 2005

In this paper, the tension of assembly stay cable connected with massive anchorage block was calculated through back analysis of in-situ frequencies measured from a stadium structure. Direct approach to back analysis is adopted using the univariate method among the direct search methods as an optimization technique. The univariate method can search the optimal tension without regard to the initial ones and has a rapid convergence rate. To verify the reliability of back analysis, Tension formulas proposed by Zui et al. and Shimada were used. Tensions estimated by three methods are compared with the design tension, and are in a reasonable agreement with an error of more or less than 15%. Therefore, it is shown that back analysis applied in this paper is appropriate for estimation of cable tension force.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.105-114
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• 2000

Job Shop Problem which consists of the m different machines and n jobs is a NP-hard problem of the combinatorial optimization. Each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. Each machine can process at most one operation at a time. The purpose of this paper is to develop the heuristic method to solve large scale scheduling problem using Constraint Satisfaction Problem method and Simulated Annealing. The proposed heuristic method consists of the search algorithm and optimization algorithm. The search algorithm is to find the solution in the solution space using CSP concept such as backtracking and domain reduction. The optimization algorithm is to search the optimal solution using SA. This method is applied to MT06, MT10 and MT20 Job Shop Problem, and compared with other heuristic method.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.187-193
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• 2005

In this paper, we proposes a man-machine interface design for fault diagnosis system with inter-node search method in a Petri net model. First, complicated fault cases are modeled as the Petri net graph expressions. Next, to find out causes of the faults on which we focus, a Petri net model is analyzed using the backward reasoning of transition-invariance in the Petri net. In this step, the inter-node search method algorithm is applied to the Petri net model for reducing the range of sources in faults. Finally, the proposed method is applied to a fault diagnosis of a refrigeration system to confirm the validity of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.6
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• pp.603-607
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• 2008

This paper proposes a fast acquisition method using INS velocity and multiple correlators for high speed vehicles. In order to reduce acquisition time in GPS receiver, the method utilizes inertial velocity information and multiple correlators. Search range of the Doppler frequency is reduced by using INS velocity and the number of cells at one search can be increased by using multiple correlators. By using both multiple correlators and the INS velocity in the acquisition, search space can be greatly reduced. Experimental results show that the method gives faster signal acquisition performance than the conventional method.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.369-370
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• 2006

This paper presents a new method for Huffman decoding specially designed for the MPEG-2 AAC audio. The method significantly enhances the processing efficiency of the conventional Huffman decoding realized with the ordinary binary tree search method. A data structure is newly designed based on the numerical interpretation of the incoming bit stream and its utilization for the offset oriented nodes allocation. The experimental results show the average performance enhancement of 54% and 665%, compared to those of the conventional binary tree search method and the sequential search method, respectively.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.11a
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• pp.435-440
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• 2004

In this paper, the tension of assembly stay cable connected with massive anchorage block was calculated through back analysis of in-situ frequencies measured from a stadium structure. Direct approach to back analysis is adopted using the univariate method among the direct search methods as an optimization technique. The univariate method can search the optimal tension without regard to the initial ones and has a rapid convergence rate. To verify the reliability of back analysis, Tension formulas proposed by Zui et al. and Shimada were used. Tensions estimated by three methods are compared with the design tension, and are in a reasonable agreement with an error of more or less than 15%. Therefore, it is shown that back analysis applied in this paper is appropriate for estimation of cable tension force.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.329-337
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• 2017

This paper proposes a search method that explores parameters C and σ values of support vector machines (SVM) to improve performance while maintaining search accuracy. A traditional grid search method requires tremendous computational times because it searches all available combinations of C and σ values to find optimal combinations which provide the best performance of SVM. To address this issue, this paper proposes a deep search method that reduces computational time. In the first stage, it divides C-σ- accurate metrics into four regions, searches a median value of each region, and then selects a point of the highest accurate value as a start point. In the second stage, the selected start points are re-divided into four regions, and then the highest accurate point is assigned as a new search point. In the third stage, after eight points near the search point. are explored and the highest accurate value is assigned as a new search point, corresponding points are divided into four parts and it calculates an accurate value. In the last stage, it is continued until an accurate metric value is the highest compared to the neighborhood point values. If it is not satisfied, it is repeated from the second stage with the input level value. Experimental results using normal and defect bearings show that the proposed deep search algorithm outperforms the conventional algorithms in terms of performance and search time.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.129-138
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• 2006

Various techniques have been applied to solve the maximal covering problem. Tabu search is also one of them. But, existing researches were lacking of the synthetic analysis and the effort for performance improvement about neighborhood search techniques such as hill-climbing search and simulated annealing including tabu search. In this paper, I introduce the way to improve performance of neighborhood search techniques through various experiments and analyses. Basically, all neighborhood search algorithms use the k-exchange neighborhood generation method. And I analyzed how the performance of each algorithm changes according to various parameter settings. Experimental results have shown that simple hill-climbing search and simulated annealing can produce better results than any other techniques. And I confirmed that simple hill-climbing search can produce similar results as simulated annealing unlike general case.