• 제목/요약/키워드: Optimal search

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구역분할 알고리즘을 이용한 다수 탐색플랫폼의 구역할당 방법 (A Methodology for Partitioning a Search Area to Allocate Multiple Platforms)

  • 안우선;조윤철;이찬선
    • 한국군사과학기술학회지
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    • 제21권2호
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    • pp.225-234
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    • 2018
  • In this paper, we consider a problem of partitioning a search area into smaller rectangular regions, so that multiple platforms can conduct search operations independently without requiring unnecessary coordination among themselves. The search area consists of cells where each cell has some prior information regarding the probability of target existence. The detection probability in particular cell is evaluated by multiplying the observation probability of the platform and the target existence probability in that cell. The total detection probability within the search area is defined as the cumulative detection probability for each cell. However, since this search area partitioning problem is NP-Hard, we decompose the problem into three sequential phases to solve this computationally intractable problem. Additionally, we discuss a special case of this problem, which can provide an optimal analytic solution. We also examine the performance of the proposed approach by comparing our results with the optimal analytic solution.

추계학적 최적화방법에 의한 기존관수로시스템의 병열관로 확장 (Stochastic Optimization Approach for Parallel Expansion of the Existing Water Distribution Systems)

  • 안태진;최계운;박정응
    • 물과 미래
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    • 제28권2호
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    • pp.169-180
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    • 1995
  • 관망상배관(Looped networks)시스템에서 관수로시스템의 전체비용은 폐회로유량(Loop flows)에 따라 영향을 받는다. 따라서 관망상배관의 최적설계를 위한 수학적모형을 추계학적 최적화방법에 적용하기 위하여 폐회로유량의 섭동(Perturbations)으로 전체비용이 변하게 하였다. 관망상 배관문제의 분석가능영역은 수많은 국지해(Local optimum)를 갖는 비볼록(Nonconvex)이므로 분석가능영역의 효율적인 심사를 위하여 수정추계학적 심사방법을 제안하였으며 이 방법은 국부심사단계(Global search phase)와 국지심사단계(Local search phase)로 구성되어 있다. 국부탐사에서는 점차적으로 국지해를 증진시키며 국지탐사에서는 국부탐사단계에서 교착상태에 있는 국지해로 부터 벗어나게 하거나 최종국지해를 증진시킨다. 제안한 방법의 효율성을 검정하기 위하여 참고문헌에 있는 기존관수로시스템의 병열관로(Parallel pipe line) 확장문제를 표본으로 채택하여 제안한 방법을 적용한 결과 먼저 발표된 연구자들의 비용보다 적은 비용으로 설계할 수 있었다.

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RG-MADS를 적용한 매입형 영구자석 동기전동기의 최적설계 (Optimal Design of Interior PM Synchronous Machines Using Randomly-Guided Mesh Adaptive Direct Search Algorithms)

  • 김광덕;이동수;정상용;김종욱;이철균
    • 전기학회논문지
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    • 제61권2호
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    • pp.216-222
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    • 2012
  • Newly proposed RG-MADS (Randomly Guided Mesh Adaptive Direct Search) has been applied to the optimal design of Interior Permanent Magnet Synchronous Motor (IPMSM) which has the distinctive features of magnetic saturation. RG-MADS, advanced from classical MADS algorithm, has the superiority in computational time and reliable convergence accuracy to the optimal solution, thus it is appropriate to the optimal design of IPMSM coupled with time-consuming Finite Element Analysis (FEA), necessary to the nonlinear magnetic application for better accuracy. Effectiveness of RG-MADS has been verified through the well-known benchmark-functions beforehand. In addition, the proposed RG-MADS has been applied to the optimal design of IPMSM aiming at maximizing the Maximum Torque Per Ampere (MTPA), which is regarded as representative design goal of IPMSM.

하모니서치 알고리즘을 이용한 반도체 공정의 최적버퍼 크기 결정 (Determination of Optimal Buffer Size for Semiconductor Production System using Harmony Search Algorithm)

  • 이병길;변민석;김여진;이종환
    • 반도체디스플레이기술학회지
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    • 제19권4호
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    • pp.39-45
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    • 2020
  • In the production process, the buffer acts as a buffer to alleviate some of the problems such as delays in delivery and process control failures in unexpected situations. Determining the optimal buffer size can contribute to system performance, such as increased output and resource utilization. However, there are difficulties in allocating the optimal buffer due to the complexity of the process or the increase in the number of variables. Therefore, the purpose of this research is proposing an optimal buffer allocation that maximizes throughput. First step is to design the production process to carry out the research. The second step is to maximize the throughput through the harmony search algorithm and to find the buffer capacity that minimizes the lead time. To verify the efficiency, comparing the ratio of the total increase in throughput to the total increase in buffer capacity.

A Tabu Search Algorithm to Optimal Weight Selection in Design of Robust $H_{\infty}$ Power System Stablilizer

  • Dechanupaprittha, S.;Ngamroo, I.
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -1
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    • pp.486-489
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    • 2002
  • This paper proposes a tabu search (TS) algorithm to optimal weight selection in design of robust H$_{\infty}$ power system stabilize. (PSS), In H$_{\infty}$ control design, the weight selection and the representation of system uncertainties are the major difficulties. To cope with these problems, TS is employed to automatically search for the optimal weights. On the other hand, the normalized coprime factorization (NCF) is used. The H$_{\infty}$ controller can be directly developed without ${\gamma}$-iteration. Also, the pole-zero cancellation phenomena are prevented. The performance and robustness of the proposed PSS under different loading conditions are investigated in comparison with a robust tuned PSS by examining the case of a single machine infinite bus (SMIB) system. The simulation results illustrate the effectiveness and robustness of the proposed PSS.

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Optimal Allocation of Distributed Solar Photovoltaic Generation in Electrical Distribution System under Uncertainties

  • Verma, Ashu;Tyagi, Arjun;Krishan, Ram
    • Journal of Electrical Engineering and Technology
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    • 제12권4호
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    • pp.1386-1396
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    • 2017
  • In this paper, a new approach is proposed to select the optimal sitting and sizing of distributed solar photovoltaic generation (SPVG) in a radial electrical distribution systems (EDS) considering load/generation uncertainties. Here, distributed generations (DGs) allocation problem is modeled as optimization problem with network loss based objective function under various equality and inequality constrains in an uncertain environment. A boundary power flow is utilized to address the uncertainties in load/generation forecasts. This approach facilitates the consideration of random uncertainties in forecast having no statistical history. Uncertain solar irradiance is modeled by beta distribution function (BDF). The resulted optimization problem is solved by a new Dynamic Harmony Search Algorithm (DHSA). Dynamic band width (DBW) based DHSA is proposed to enhance the search space and dynamically adjust the exploitation near the optimal solution. Proposed approach is demonstrated for two standard IEEE radial distribution systems under different scenarios.

Optimal ECO-Design of Permanent Magnet Brushless DC Motor Using Modified Tabu Search Optimizer and Finite Element Analysis

  • Yazdani-Asrami, Mohammad;Alipour, Mohammad;Gholamian, S. Asghar
    • Journal of Magnetics
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    • 제20권2호
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    • pp.161-165
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    • 2015
  • The Permanent Magnet Brushless DC (PMBLDC) motors have been used in modern industrial factories, hazardous chemical process, modern medical devices, and especially in advanced military devices such as army drones. By considering their sensitive role in the industrial and military applications, their optimal design has a real concern. This paper proposes a method for optimal eco-design of a PMBLDC motor using improved tabu search optimization. The objective function is based on losses, volume and cost. Electrical and mechanical requirements and other limitations are combined into constraints of problem. Also, finite element analysis has been used for verifications in magnetic mode.

Optimal distribution of metallic energy dissipation devices in multi-story buildings via local search heuristics

  • Zongjing, Li;Ganping, Shu;Zhen, Huang;Jing, Cao
    • Earthquakes and Structures
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    • 제23권5호
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    • pp.419-430
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    • 2022
  • The metallic energy dissipation device (EDD) has been widely accepted as a useful tool for passive control of buildings against earthquakes. The distribution of metallic EDDs in a multi-story building may have significant influence on its seismic performance, which can be greatly enhanced if the distribution scheme is properly designed. This paper addresses the optimal distribution problem in the aim of achieving a desired level of performance using the minimum number of metallic EDDs. Five local search heuristic algorithms are proposed to solve the problem. Four base structures are presented as numerical examples to verify the proposed algorithms. It is indicated that the performance of different algorithms may vary when applied in different situations. Based on the results of the numerical verification, the recommended guidelines are finally proposed for choosing the appropriate algorithm in different occasions.

Subset selection in multiple linear regression: An improved Tabu search

  • Bae, Jaegug;Kim, Jung-Tae;Kim, Jae-Hwan
    • Journal of Advanced Marine Engineering and Technology
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    • 제40권2호
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    • pp.138-145
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    • 2016
  • This paper proposes an improved tabu search method for subset selection in multiple linear regression models. Variable selection is a vital combinatorial optimization problem in multivariate statistics. The selection of the optimal subset of variables is necessary in order to reliably construct a multiple linear regression model. Its applications widely range from machine learning, timeseries prediction, and multi-class classification to noise detection. Since this problem has NP-complete nature, it becomes more difficult to find the optimal solution as the number of variables increases. Two typical metaheuristic methods have been developed to tackle the problem: the tabu search algorithm and hybrid genetic and simulated annealing algorithm. However, these two methods have shortcomings. The tabu search method requires a large amount of computing time, and the hybrid algorithm produces a less accurate solution. To overcome the shortcomings of these methods, we propose an improved tabu search algorithm to reduce moves of the neighborhood and to adopt an effective move search strategy. To evaluate the performance of the proposed method, comparative studies are performed on small literature data sets and on large simulation data sets. Computational results show that the proposed method outperforms two metaheuristic methods in terms of the computing time and solution quality.

Design and optimization of steel trusses using genetic algorithms, parallel computing, and human-computer interaction

  • Agarwal, Pranab;Raich, Anne M.
    • Structural Engineering and Mechanics
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    • 제23권4호
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    • pp.325-337
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    • 2006
  • A hybrid structural design and optimization methodology that combines the strengths of genetic algorithms, local search techniques, and parallel computing is developed to evolve optimal truss systems in this research effort. The primary objective that is met in evolving near-optimal or optimal structural systems using this approach is the capability of satisfying user-defined design criteria while minimizing the computational time required. The application of genetic algorithms to the design and optimization of truss systems supports conceptual design by facilitating the exploration of new design alternatives. In addition, final shape optimization of the evolved designs is supported through the refinement of member sizes using local search techniques for further improvement. The use of the hybrid approach, therefore, enhances the overall process of structural design. Parallel computing is implemented to reduce the total computation time required to obtain near-optimal designs. The support of human-computer interaction during layout optimization and local optimization is also discussed since it assists in evolving optimal truss systems that better satisfy a user's design requirements and design preferences.