• 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.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.21-31
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• 2005

In state-of-the-art games, characters can move in a goal-directed manner so that they can move to the goal position without colliding obstacles. Many path-finding methods have been proposed and implemented for these characters and most of them use the A* search algorithm. When .the map is represented with a regular grid of squares or a navigation mesh, it often takes a long time for the A* to search the state space because the number of cells used In the grid or the mesh increases for higher resolution. Moreover the A* search on the grid often causes a zigzag effect, which is not optimal and realistic. In this paper we propose to use visibility graphs to improve the search time by reducing the search space and to find the optimal path. We also propose a method of taking into account the size of moving characters in the phase of planning to prevent them from colliding with obstacles as they move. Simulation results show that the proposed method performs better than the grid-based A* algorithm in terms of the search time and space and that the resulting paths are more realistic.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.1
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• pp.62-68
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• 1999

The attitude of a vehicle can be precisely determined using GPS carrier phase measurements from more than two antennas attached to a vehicle and an efficient integer ambiguity resolution technique. Many methods utilizing the known baseline length as a constraint of independent elements of integer ambiguities are proposed to resolve integer ambiguity at real time. Three-dimensional search space is reduced to two-dimensional search space with this constraint. Thus the true integer ambiguity can be easily determined with less computational burden and fewer number of measurements. But there are still strong requirements for the real time integer ambiguity resolution, which uses single epoch measurement of long baseline. In this paper, a new constraint from the geometry of multiple baselines is derived. With this new constraint, two-dimensional search space is further reduced to one-dimensional search space. It makes possible to determine integer ambiguity with single epoch measurement. The proposed method is applied to real data to show its effectiveness.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.233-238
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• 2003

Living creatures maintain their variety through speciation, which helps them to have more fitness for an environment. So evolutionary algorithm based on biological evolution must maintain variety in order to adapt to its environment. In this paper, we utilize the concept of speciation. Each individual of population creates their offsprings using mutation, and next generation consists of them. Each individual explores search space determined by mutation. Useful search space is extended by differentiation, then population explorers whole search space very effectively. If evolvable hardware evolves through mutation, it is useful way to explorer search space because of less varying inner structure. We verify the effectiveness of the proposed method by applying it to two optimization problems.

• Advances in Computational Design
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• v.1 no.2
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• pp.175-194
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• 2016

Nature has provided inspiration for most of the man-made technologies. Scientists believe that dolphins are the second to humans in smartness and intelligence. Echolocation is the biological sonar used by dolphins for navigation and hunting in various environments. This ability of dolphins is mimicked in this paper to develop a new optimization method. Dolphin Echolocation Optimization (DEO) is an optimization method based on dolphin's approach for hunting food and exploration of environment. DEO has already been developed for discrete optimization search space and here it is extended to continuous search space. DEO has simple rules and is adjustable for predetermined computational cost. DEO provides the optimum results and leads to alternative optimality curves suitable for the problem. This algorithm has a few parameters and it is applicable to a wide range of problems like other metaheuristic algorithms. In the present work, the efficiency of this approach is demonstrated using standard benchmark problems.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.686-691
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• 2011

This study is concerned with the identification of fuzzy models. To address the optimization of fuzzy model, we proposed an improved space search evolutionary algorithm (ISSA) which is realized with the combination of space search algorithm and Gaussian mutation. The proposed ISSA is exploited here as the optimization vehicle for the design of fuzzy models. Considering the design of fuzzy models, we developed a hybrid identification method using information granulation and the ISSA. Information granules are treated as collections of objects (e.g. data) brought together by the criteria of proximity, similarity, or functionality. The overall hybrid identification comes in the form of two optimization mechanisms: structure identification and parameter identification. The structure identification is supported by the ISSA and C-Means while the parameter estimation is realized via the ISSA and weighted least square error method. A suite of comparative studies show that the proposed model leads to better performance in comparison with some existing models.

• Journal of Information Processing Systems
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• v.9 no.2
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• pp.315-332
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• 2013

This paper presents an approach for improving the use of VP-tree in video indexing and searching. A vantage-point tree or VP-tree is one of the metric space-based indexing methods used in multimedia database searches and data retrieval. Instead of relying on the Euclidean distance as a measure of search space, the proposed approach focuses on the trigonometric inequality for compressing the search range, which thus, improves the search performance. A test result of using 10,000 video files shows that this method reduced the search time by 5-12%, as compared to the existing method that uses the AESA algorithm.

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.153-167
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• 2005

In this paper, we consider the problem of exploring unknown environments with a mobile robot or an autonomous character agent. Traditionally, research efforts to address the space exploration problem havefocused on the graph-based space representations and the graph search algorithms. Recently EXPLORE, one of the most efficient search algorithms, has been discovered. It traverses at most min$min(mn, d^2+m)$ edges where d is the deficiency of a edges and n is the number of edges and n is the number of vertices. In this paper, we propose DFS-RTA* and DFS-PHA*, two real-time graph search algorithms for directing an autonomous agent to explore in an unknown space. These algorithms are all built upon the simple depth-first search (DFS) like EXPLORE. However, they adopt different real-time shortest path-finding methods for fast backtracking to the latest node, RTA* and PHA*, respectively. Through some experiments using Unreal Tournament, a 3D online game environment, and KGBot, an intelligent character agent, we analyze completeness and efficiency of two algorithms.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.500-503
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• 2003

The navigation problem of robot is one of the main themes to deal with conficts or interferences between obstacles and the robot itself In this case, while the robot avoids obstacles on the space, the passage route should be determined efficiently. In order to solve problems above, we have come up with the distance field space medel (DFM) and then, under known environment, we have presented the distance field A algorithm for passage route path search. In this research, the method of performing the 3-dimensional passage route path search of robot under unknown environment is proposed. It is shown that the authors can build the distance search model the does not need space division by taking into account of sensor information to a distance field space model, and constructing this information as virtual obstacle information.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.5
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• pp.260-267
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• 2005

To search efficiently a text T of length n for a pattern P over an alphabet 5, suffix trees and suffix arrays are widely used. In case of a large text, suffix arrays are preferred to suffix trees because suffix ways take less space than suffix trees. Recently, O(${\mid}P{\mid}{\codt}{\mid}{\Sigma}{\mid}$-time and O(${\mid}P{\mid}P{\cdot}log{\mid}{\Sigma}{\mid}$)-time search algorithms in suffix ways were developed. In this paper we present time and space efficient search algorithms in suffix arrays. One algorithm runs in O(${\mid}P{\mid}$) time using O($n{\cdot}{\mid}{\Sigma}{\mid}$)-bits space, and the other runs in O($n{\cdot}{\mid}{\Sigma}{\mid}$ time using O($nlog{\mid}{\Sigma}{\mid}+{\mid}{\Sigma}{\mid}{\cdot}$nlog log n/logn)-bits space, which is more space efficient and still fast. Experiments show that our algorithms are efficient in both time and space when compared to previous algorithms.