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MODIFIED LIMITED MEMORY BFGS METHOD WITH NONMONOTONE LINE SEARCH FOR UNCONSTRAINED OPTIMIZATION

  • Yuan, Gonglin;Wei, Zengxin;Wu, Yanlin
    • Journal of the Korean Mathematical Society
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    • v.47 no.4
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    • pp.767-788
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    • 2010
  • In this paper, we propose two limited memory BFGS algorithms with a nonmonotone line search technique for unconstrained optimization problems. The global convergence of the given methods will be established under suitable conditions. Numerical results show that the presented algorithms are more competitive than the normal BFGS method.

Development of Hybrid Vision Correction Algorithm (Hybrid Vision Correction Algorithm의 개발)

  • Ryu, Yong Min;Lee, Eui Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.1
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    • pp.61-73
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    • 2021
  • Metaheuristic search methods have been developed to solve problems with a range of purpose functions in situations lacking information and time constraints. In this study, the Hybrid Vision Correction Algorithm (HVCA), which enhances the performance of the Vision Correction Algorithm (VCA), was developed. The HVCA has applied two methods to improve the performance of VCA. The first method changes the parameters required by the user for self-adaptive parameters. The second method, the CGS structure of the Exponential Bandwidth Harmony Search With a Centralized Global Search (EBHS-CGS), was added to the HVCA. The HVCA consists of two structures: CGS and VCA. To use the two structures, a method was applied to increase the probability of selecting the structure with the optimal value as it was performed. The optimization problem was applied to determine the performance of the HVCA, and the results were compared with Harmony Search (HS), Improved Harmony Search (IHS), and VCA. The HVCA improved the number of times to find the optimal value during 100 repetitions compared to HS, IHS, and VCA. Moreover, the HVCA reduced the Number of Function Evaluations (NFEs). Therefore, the performance of the HVCA has been improved.

A General Tool Surface Contact Search and its Application to 3-D Deep drawing Process (일반적인 금형면에서의 접촉탐색과 3차원 디프드로잉 성형에의 응용)

  • 서의권;심현보
    • Transactions of Materials Processing
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    • v.6 no.5
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    • pp.416-424
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    • 1997
  • In the present study, a contact search and check algorithm for general tool surface described by triangular FE patch is proposed. To improve numerical stability, SEAM element using the linear Coons interpolation has been used. To check the proposed algorithm, both clover cup and L-shape cup deep drawing processes are calculated. The computed results shows that the proposed contact algorithm can be successfully applied for sheet metal forming processes with general shaped tools.

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Ooptimum Design Damping Plate by Combined Method of Genetic Algorithm and Random Tabu Search Method (유전알고리즘과 Tabu탐색법에 의한 제진판의 최적설계)

  • 양보석;전상범;유영훈;최병근
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1997.10a
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    • pp.184-189
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    • 1997
  • This paper introduces a new combined method by genetic algorithm and random tabu search method as optimization algorithm. Genetic algorithm can search the global optimum and tabu search method is very fast in speed. The optimizing ability of new combined method is identified by comparing other optimizing algorithm and used for optimum design of damping plate.

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A new hybrid optimization algorithm based on path projection

  • Gharebaghi, Saeed Asil;Ardalan Asl, Mohammad
    • Structural Engineering and Mechanics
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    • v.65 no.6
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    • pp.707-719
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    • 2018
  • In this article, a new method is introduced to improve the local search capability of meta-heuristic algorithms using the projection of the path on the border of constraints. In a mathematical point of view, the Gradient Projection Method is applied through a new approach, while the imposed limitations are removed. Accordingly, the gradient vector is replaced with a new meta-heuristic based vector. Besides, the active constraint identification algorithm, and the projection method are changed into less complex approaches. As a result, if a constraint is violated by an agent, a new path will be suggested to correct the direction of the agent's movement. The presented procedure includes three main steps: (1) the identification of the active constraint, (2) the neighboring point determination, and (3) the new direction and step length. Moreover, this method can be applied to some meta-heuristic algorithms. It increases the chance of convergence in the final phase of the search process, especially when the number of the violations of the constraints increases. The method is applied jointly with the authors' newly developed meta-heuristic algorithm, entitled Star Graph. The capability of the resulted hybrid method is examined using the optimal design of truss and frame structures. Eventually, the comparison of the results with other meta-heuristics of the literature shows that the hybrid method is successful in the global as well as local search.

Structural damage identification based on modified Cuckoo Search algorithm

  • Xu, H.J.;Liu, J.K.;Lv, Z.R.
    • Structural Engineering and Mechanics
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    • v.58 no.1
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    • pp.163-179
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    • 2016
  • The Cuckoo search (CS) algorithm is a simple and efficient global optimization algorithm and it has been applied to figure out large range of real-world optimization problem. In this paper, a new formula is introduced to the discovering probability process to improve the convergence rate and the Tournament Selection Strategy is adopted to enhance global search ability of the certain algorithm. Then an approach for structural damage identification based on modified Cuckoo search (MCS) is presented. Meanwhile, we take frequency residual error and the modal assurance criterion (MAC) as indexes of damage detection in view of the crack damage, and the MCS algorithm is utilized to identifying the structural damage. A simply supported beam and a 31-bar truss are studied as numerical example to illustrate the correctness and efficiency of the propose method. Besides, a laboratory work is also conducted to further verification. Studies show that, the proposed method can judge the damage location and degree of structures more accurately than its counterpart even under measurement noise, which demonstrates the MCS algorithm has a higher damage diagnosis precision.

Hybrid Approach for Solving Manufacturing Optimization Problems (제조최적화문제 해결을 위한 혼합형 접근법)

  • Yun, YoungSu
    • Journal of Korea Society of Industrial Information Systems
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    • v.20 no.6
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    • pp.57-65
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    • 2015
  • Manufacturing optimization problem is to find the optimal solution under satisfying various and complicated constraints with the design variables of nonlinear types. To achieve the objective, this paper proposes a hybrid approach. The proposed hybrid approach is consist of genetic algorithm(GA), cuckoo search(CS) and hill climbing method(HCM). First, the GA is used for global search. Secondly, the CS is adapted to overcome the weakness of GA search. Lastly, the HCM is applied to search precisely the convergence space after the GA and CS search. In experimental comparison, various types of manufacturing optimization problems are used for comparing the efficiency between the proposed hybrid approach and other conventional competing approaches using various measures of performance. The experimental result shows that the proposed hybrid approach outperforms the other conventional competing approaches.

Design Optimization for Loop Heat Pipe Using Tabu Search (Tabu Search를 이용한 Loop Heat Pipe의 최적설계에 관한 연구)

  • Park, Yong-Jin;Yun, Su-Hwan;Ku, Yo-Cheun;Lee, Dong-Ho
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.37 no.8
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    • pp.737-743
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    • 2009
  • Design optimization process and results of Loop Heat Pipe(LHP) using Tabu Search have been presented in this study. An objective of optimization is to reduce a mass of the LHP with satisfying operating temperature of a Lithium Ion battery onboard an aircraft. The battery is assumed to be used as power supply of air borne high energy laser system because of its high specific energy. The analytical models are based on a steady state mathematical model and the design optimization is performed using a Meta Model and Tabu Search. As an optimization results, the Tabu search algorithm guarantees global optimum with small computation time. Due to searching by random numbers, initial value is dominant factor to search global optimum. The optimization process could reduce the mass of the LHP which express the same performance as an published LHP.

Multi-objective optimization of foundation using global-local gravitational search algorithm

  • Khajehzadeh, Mohammad;Taha, Mohd Raihan;Eslami, Mahdiyeh
    • Structural Engineering and Mechanics
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    • v.50 no.3
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    • pp.257-273
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    • 2014
  • This paper introduces a novel optimization technique based on gravitational search algorithm (GSA) for numerical optimization and multi-objective optimization of foundation. In the proposed method, a chaotic time varying system is applied into the position updating equation to increase the global exploration ability and accurate local exploitation of the original algorithm. The new algorithm called global-local GSA (GLGSA) is applied for optimization of some well-known mathematical benchmark functions as well as two design examples of spread foundation. In the foundation optimization, two objective functions include total cost and $CO_2$ emissions of the foundation subjected to geotechnical and structural requirements are considered. From environmental point of view, minimization of embedded $CO_2$ emissions that quantifies the total amount of carbon dioxide emissions resulting from the use of materials seems necessary to include in the design criteria. The experimental results demonstrate that, the proposed GLGSA remarkably improves the accuracy, stability and efficiency of the original algorithm.

Seamless Routing and Cooperative Localization of Multiple Mobile Robots for Search and Rescue Application

  • Lee, Chang-Eun;Im, Hyun-Ja;Lim, Jeong-Min;Cho, Young-Jo;Sung, Tae-Kyung
    • ETRI Journal
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    • v.37 no.2
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    • pp.262-272
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    • 2015
  • In particular, for a practical mobile robot team to perform such a task as that of carrying out a search and rescue mission in a disaster area, the network connectivity and localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a Global Positioning System is unavailable. This paper proposes the new collective intelligence network management architecture of multiple mobile robots supporting seamless network connectivity and cooperative localization. The proposed architecture includes a resource manager that makes the robots move around and not disconnect from the network link by considering the strength of the network signal and link quality. The location manager in the architecture supports localizing robots seamlessly by finding the relative locations of the robots as they move from a global outdoor environment to a local indoor position. The proposed schemes assuring network connectivity and localization were validated through numerical simulations and applied to a search and rescue robot team.