• Title/Summary/Keyword: Global search method

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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.

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.

Vibration Optimization Design of Ship Structure Using NASTRAN-based R-Tabu Search Method (NASTRAN 기반 R-Tabu 탐색법을 이용한 선박구조물의 진동최적설계)

  • 채상일;송진대;김용한;공영모;최수현;양보석
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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    • pp.672-676
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    • 2003
  • Recently, the importance of ship vibration is emerging due to the large scaling, high speed and lightning of ship. For pleasantness in a cabin, shipbuilders ask for strict vibration criteria and the degree of vibration level at a deckhouse became an important condition for taking order from customers. This study conducted optimum design to attenuate vibration level of a deckhouse to solve above problems. New method was implemented, that is NASTRAN external call type independence optimization method. The merit of this method is global searching after setting various object functions and design variables. The global optimization algorithm used here is R-Tabu search method, which has fast converging time and searching various size domains. By modeling similar type to ship structure, validity of the suggested method was investigated.

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A Hybrid Search Method Based on the Artificial Bee Colony Algorithm (인공벌 군집 알고리즘을 기반으로 한 복합탐색법)

  • Lee, Su-Hang;Kim, Il-Hyun;Kim, Yong-Ho;Han, Seog-Young
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.23 no.3
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    • pp.213-217
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    • 2014
  • A hybrid search method based on the artificial bee colony algorithm (ABCA) with harmony search (HS) is suggested for finding a global solution in the field of optimization. Three cases of the suggested algorithm were examined for improving the accuracy and convergence rate. The results showed that the case in which the harmony search was implemented with the onlooker phase in ABCA was the best among the three cases. Although the total computation time of the best case is a little bit longer than the original ABCA under the prescribed conditions, the global solution improved and the convergence rate was slightly faster than those of the ABCA. It is concluded that the suggested algorithm improves the accuracy and convergence rate, and it is expected that it can effectively be applied to optimization problems with many design variables and local solutions.

An Enhanced Genetic Algorithm for Global and Local Optimization Search (전역 및 국소 최적화탐색을 위한 향상된 유전 알고리듬의 제안)

  • Kim, Young-Chan;Yang, Bo-Suk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.6
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    • pp.1008-1015
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    • 2002
  • This paper proposes a combinatorial method to compute the global and local solutions of optimization problem. The present hybrid algorithm is the synthesis of a genetic algorithm and a local concentrate search algorithm (simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm, but also gives a more accurate solution. In addition, this algorithm can find both the global and local optimum solutions. An optimization result is presented to demonstrate that the proposed approach successfully focuses on the advantages of global and local searches. Three numerical examples are also presented in this paper to compare with conventional methods.

A Global Optimization Technique for the Capacitor Placement in Distribution Systems (배전계통 커패시터 설치를 위한 전역적 최적화 기법)

  • Rhee, Sang-Bong;Kim, Kyu-Ho;Lee, Sang-Keun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.5
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    • pp.748-754
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    • 2008
  • The general capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints. In this paper, a global optimization technique, which employing the chaos search algorithm, is applied to solve optimal capacitor placement problem with reducing computational effort and enhancing global optimality of the solution. Chaos method in optimization problem searches the global optimal solution on the regularity of chaotic motions and easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos optimization method is tested on 9 buses and 69 buses system to illustrate the effectiveness of the proposed method.

An Improved Artificial Bee Colony Algorithm Based on Special Division and Intellective Search

  • Huang, He;Zhu, Min;Wang, Jin
    • Journal of Information Processing Systems
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    • v.15 no.2
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    • pp.433-439
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    • 2019
  • Artificial bee colony algorithm is a strong global search algorithm which exhibits excellent exploration ability. The conventional ABC algorithm adopts employed bees, onlooker bees and scouts to cooperate with each other. However, its one dimension and greedy search strategy causes slow convergence speed. To enhance its performance, in this paper, we abandon the greedy selection method and propose an artificial bee colony algorithm with special division and intellective search (ABCIS). For the purpose of higher food source research efficiency, different search strategies are adopted with different employed bees and onlooker bees. Experimental results on a series of benchmarks algorithms demonstrate its effectiveness.

Analysis of Global Oscillation via Sync Search in Power Systems (전력계통에서 동조탐색과 광역진동해석)

  • Shim, Kwan-Shik;Nam, Hae-Kon;Kim, Yong-Gu;Moon, Young-Hoan;Kim, Sang-Tae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.7
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    • pp.1255-1262
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    • 2009
  • The present study explained the phenomenon that low frequency oscillation is synchronized with discrete data obtained from a wide area system, and a sync search method. When a disturbance occurs in an power system, various controllers operate in order to maintain synchronization. If the system's damping is poor, low frequency oscillations continue for a long time and the oscillations are synchronized with one another at specific frequency. The present study estimated dominant modes, magnitude and phase of signals by applying parameter estimation methods to discrete signals obtained from an power system, and performed sync search among wide area signals by comparing the estimated data. Sync search was performed by selecting those with the same frequency and damping constant from dominant oscillation modes included in a large number of signals, and comparing their magnitude and phase. In addition, we defined sync indexes in order to indicate the degree of sync between areas in a wide area system. Furthermore, we proposed a wide area sync search method by normalizing mode magnitude in discrete data obtained from critical generator of the wide area. By applying the sync search method and sync indexes proposed in this study to two area systems, we demonstrated that sync scanning can be performed for discrete signals obtained from power systems.

Development of Pareto strategy multi-objective function method for the optimum design of ship structures

  • Na, Seung-Soo;Karr, Dale G.
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.8 no.6
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    • pp.602-614
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    • 2016
  • It is necessary to develop an efficient optimization technique to perform optimum designs which have given design spaces, discrete design values and several design goals. As optimization techniques, direct search method and stochastic search method are widely used in designing of ship structures. The merit of the direct search method is to search the optimum points rapidly by considering the search direction, step size and convergence limit. And the merit of the stochastic search method is to obtain the global optimum points well by spreading points randomly entire the design spaces. In this paper, Pareto Strategy (PS) multi-objective function method is developed by considering the search direction based on Pareto optimal points, the step size, the convergence limit and the random number generation. The success points between just before and current Pareto optimal points are considered. PS method can also apply to the single objective function problems, and can consider the discrete design variables such as plate thickness, longitudinal space, web height and web space. The optimum design results are compared with existing Random Search (RS) multi-objective function method and Evolutionary Strategy (ES) multi-objective function method by performing the optimum designs of double bottom structure and double hull tanker which have discrete design values. Its superiority and effectiveness are shown by comparing the optimum results with those of RS method and ES method.

Discrete Optimization of Plane Frame Structures Using Genetic Algorithms (유전자 알고리즘을 이용한 뼈대구조물의 이산최적화)

  • 김봉익;권중현
    • Journal of Ocean Engineering and Technology
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    • v.16 no.4
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    • pp.25-31
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    • 2002
  • This paper is to find optimum design of plane framed structures with discrete variables. Global search algorithms for this problem are Genetic Algorithms(GAs), Simulated Annealing(SA) and Shuffled Complex Evolution(SCE), and hybrid methods (GAs-SA, GAs-SCE). GAs and SA are heuristic search algorithms and effective tools which is finding global solution for discrete optimization. In particular, GAs is known as the search method to find global optimum or near global optimum. In this paper, reinforced concrete plane frames with rectangular section and steel plane frames with W-sections are used for the design of discrete optimization. These structures are designed for stress constraints. The robust and effectiveness of Genetic Algorithms are demonstrated through several examples.