• 전기학회논문지
• /
• 제58권4호
• /
• pp.840-848
• /
• 2009

This paper proposes a new multi-start scheme that generates guided random bits in selecting initial search points for global optimization with univariate dynamic encoding algorithm for searches (uDEAS). The proposed method counts the number of 1 in each bit position from all the previously generated initial search matrices and, based on this information, generates 0 in proportion with the probability of selecting 1. This rule is simple and effective for improving diversity of initial search points. The performance improvement of the proposed multi-start is validated through implementation in uDEAS and function optimization experiments.

• Structural Engineering and Mechanics
• /
• 제37권5호
• /
• pp.543-560
• /
• 2011

In structural engineering there are randomness inherently exist on determination of the loads, strength, geometry, and so on, and the manufacturing of the structural members, workmanship etc. Thus, objective and constraint functions of the optimization problem are functions that depend on those randomly natured components. The constraints being the function of the random variables are evaluated by using reliability index or performance measure approaches in the optimization process. In this study, the minimum weight of a space truss is obtained under the uncertainties on the load, material and cross-section areas with harmony search using reliability index and performance measure approaches. Consequently, optimization algorithm produces the same result when both the approaches converge. Performance measure approach, however, is more efficient compare to reliability index approach in terms of the convergence rate and iterations needed.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제5권1호
• /
• pp.21-28
• /
• 2005

This paper proposes a new method for accelerating the search speed of genetic algorithms by taking derivative evaluation and conditional random selection into account in their evolution process. Derivative evaluation makes genetic algorithms focus on the individuals whose fitness is rapidly increased. This accelerates the search speed of genetic algorithms by enhancing exploitation like steepest descent methods but also increases the possibility of a premature convergence that means most individuals after a few generations approach to local optima. On the other hand, derivative evaluation under a premature convergence helps genetic algorithms escape the local optima by enhancing exploration. If GAs fall into a premature convergence, random selection is used in order to help escaping local optimum, but its effects are not large. We experimented our method with one combinatorial problem and five complex function optimization problems. Experimental results showed that our method was superior to the simple genetic algorithm especially when the search space is large.

• 대한기계학회논문집
• /
• 제19권2호
• /
• pp.433-442
• /
• 1995

For the line search of a multi-variable optimization, an efficient algorithm is presented. The algorithm sequentially employs several polynomial approximations such as 2-point quadratic interpolation, 3-point cubic interpolation/extrapolation and 4-point cubic interpolation/extrapolation. The order of polynomial function is automatically increased for improving the accuracy of approximation. The method of approximation (interpolation or extrapolation) is automatically switched by checking the slope information of the sample points. Also, for selecting the initial step length along the descent vector, a new approach is presented. The performance of the proposed method is examined by solving typical test problems such as mathematical problems, mechanical design problems and dynamic response problems.

• Structural Engineering and Mechanics
• /
• 제60권4호
• /
• pp.729-747
• /
• 2016

This study aims to present a novel optimization algorithm known as gravitational search algorithm (GSA) for structural damage detection. An objective function for damage detection is established based on structural vibration data in frequency domain, i.e., natural frequencies and mode shapes. The feasibility and efficiency of the GSA are testified on three different structures, i.e., a beam, a truss and a plate. Results show that the proposed strategy is efficient for determining the locations and the extents of structural damages using the first several modal data of the structure. Multiple damages cases in different types of structures are studied and good identification results can be obtained. The effect of measurement noise on the identification results is investigated.

• Smart Structures and Systems
• /
• 제19권4호
• /
• pp.449-461
• /
• 2017

One of the most recent methods of structural damage identification is using the difference between structures responses after and before damage occurrence. To do this one can formulate the damage detection problem as an inverse optimization problem where the extents of damage in each element are considered as the optimizations variables. To optimize the objective function, heuristic methods such as GA, PSO etc. are widely utilized. In this paper, inspired by animals such as bat, dolphin, oilbird, shrew etc. that use echolocation for finding food, a new and efficient method, called Echolocation Search Algorithm (ESA), is proposed to properly identify the site and extent of multiple damage cases in structural systems. Numerical results show that the proposed method can reliably determine the location and severity of multiple damage cases in structural systems.

• 한국측량학회:학술대회논문집
• /
• 한국측량학회 2004년도 추계학술발표회 논문집
• /
• pp.479-484
• /
• 2004

It is the present situation that the relevant data with the compensation and payment is filed and managed in the form of document or Excell. In case of the large volume dam construction, the management of the data about the sinking areas is conducted inefficiently in view of time management and economy through using the administrative manpower and data formating manpower. There is also problem about where and how to keep the data owing to the enormous data. As a result of the raised questions, through constructing the system which is linked with the location information and property information which is relevant to the compensation to increase the applying value of the information about the compensation and apply document management system to the geographic information system, the management system through computerizing for searching the uncompensated areas in appropriate areas and compensation information in the compensated areas is projected. Through constructing geographic information system, it is expected to create various information effects, using the function of the necessary area search for the boundary survey, actual condition survey, uncompensated area search, and re-compensated area search.

• 한국정보과학회논문지:데이타베이스
• /
• 제31권2호
• /
• pp.83-90
• /
• 2004

본 논문에서는 순환적인 검색공간과 장애물이 존재하는 검색공간에서 객체들을 클러스터링할 때 고려해야하는 CCD(Clustering with Circular Distance) 문제와 COD(Clustering with Obstructed Distance) 문제를 연구하였다. 그리고 다차원 검색공간에서 삽입이나 삭제가 빈번히 발생하는 객체들을 효율적으로 클러스터링하기 위한 새로운 클러스터링 알고리즘을 제안하였다. 제안한 클러스터링 알고리즘에는 CCD 및 COD 문제를 해결하기 위한 거리 함수가 정의된다. 그리고 최소의 연산 시간으로 높은 공간 국부성을 갖는 클러스터들을 생성하기 위한 클러스터링 방법이 포함된다.

• 디지털콘텐츠학회 논문지
• /
• 제11권1호
• /
• pp.39-45
• /
• 2010

본 논문에서는 기울기 기반 빠른 정상점 탐색 방법론을 제시하고 시뮬레이션 결과를 제시한다. 제안하는 방법론은 유한 구간에서 단봉 그래프를 가지는 함수의 정상점(최대치)을 최대한 적은 수의 함수값을 참조하여 찾는 문제에 대한 솔루션으로, 대표적인 적용분야로는 자동초점이 있다. 우리는 정상점 탐색을 위해 주기적 탐색, 기울기 기반 탐색, 상세 탐색과 같이 세가지 탐색 전략을 통해 정상점을 찾는다. 노이즈가 첨가된 가우시안 함수를 발생시켜 시뮬레이션 한 결과 대략 8번탐색 횟수와 1.04의 오차를 보임을 알 수 있었다.

• 한국컴퓨터정보학회논문지
• /
• 제20권9호
• /
• pp.21-29
• /
• 2015

The set partitioning problem is a well-known NP-hard combinatorial optimization problem, and it is formulated as an integer programming model. This paper proposes an Integer Programming-based Local Search for solving the set partitioning problem. The key point is to solve the set partitioning problem as the set covering problem. First, an initial solution is generated by a simple heuristic for the set covering problem, and then the solution is set as the current solution. Next, the following process is repeated. The original set covering problem is reduced based on the current solution, and the reduced problem is solved by Integer Programming which includes a specific element in the objective function to derive the solution for the set partitioning problem. Experimental results on a set of OR-Library instances show that the proposed algorithm outperforms pure integer programming as well as the existing heuristic algorithms both in solution quality and time.