• Title/Summary/Keyword: SA algorithm

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Efficient Algorithms for Solving Facility Layout Problem Using a New Neighborhood Generation Method Focusing on Adjacent Preference

  • Fukushi, Tatsuya;Yamamoto, Hisashi;Suzuki, Atsushi;Tsujimura, Yasuhiro
    • Industrial Engineering and Management Systems
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    • v.8 no.1
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    • pp.22-28
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    • 2009
  • We consider facility layout problems, where mn facility units are assigned into mn cells. These cells are arranged into a rectangular pattern with m rows and n columns. In order to solve this cell type facility layout problem, many approximation algorithms with improved local search methods were studied because it was quite difficult to find exact optimum of such problem in case of large size problem. In this paper, new algorithms based on Simulated Annealing (SA) method with two neighborhood generation methods are proposed. The new neighborhood generation method adopts the exchanging operation of facility units in accordance with adjacent preference. For evaluating the performance of the neighborhood generation method, three algorithms, previous SA algorithm with random 2-opt neighborhood generation method, the SA-based algorithm with the new neighborhood generation method (SA1) and the SA-based algorithm with probabilistic selection of random 2-opt and the new neighborhood generation method (SA2), are developed and compared by experiment of solving same example problem. In case of numeric examples with problem type 1 (the optimum layout is given), SA1 algorithm could find excellent layout than other algorithms. However, in case of problem type 2 (random-prepared and optimum-unknown problem), SA2 was excellent more than other algorithms.

A Development of GPS Navigation Algorithm After SA Fade Away (고의잡음(SA)의 제거를 고려한 GPS 항법 알고리즘의 개발)

  • Park, Sun;Im, Yeong-Jae;Park, Chan-Sik
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.100-100
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    • 2000
  • In this paper, a new GPS navigation algorithm which considering the SA fade away, is proposed. Ionospheric delay and Tropospheric: delay is modeled and estimated is the proposed method. The experimental results show that precise positioning without DGPS or other sensors can be possible. It will be easily applied to car or marine navigation without changes.

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Synthesis of binary phase computer generated hologram by usngin an efficient simulated annealing algorithm (효율적인 Simulated Annealing 알고리듬을 이용한 이진 위상 컴퓨터형성 홀로그램의 합성)

  • 김철수;김동호;김정우;배장근;이재곤;김수중
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.32A no.2
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    • pp.111-119
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    • 1995
  • In this paper, we propose an efficient SA(simulated annealing) algorithm for the synthesis of binary phase computer generated hologram. SA algorithm is a method to find the optimal solution through iterative technique. It is important that selecting cost function and parameters within this algorithm. The aplications of converentional SA algorithm to synthesize parameters within this algorithm. The applications of conventional SA algorithm to synthesize binary hologram have many problems because of inappropriate paramters and cost function. So, we propose a new cost function and a calculation technique of proper parameters required to achieve the optimal solution. Computer simulation results show that the proposed method is better than conventional method in terms of diffraction efficiency and reconstruction error. Also, we show the reconstructed images by the proposed method through optical esperiment.

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Cooling Schedules in Simulated Annealing Algorithms for Optimal Seismic Design of Plane Frame Structures (평면골조의 최적내진설계를 위한 SA 알고리즘의 냉각스케줄)

  • 이상관;박효선;박성무
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2000.04b
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    • pp.458-465
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    • 2000
  • In the field of structural optimization simulated annealing (SA) algorithm has widely been adopted as an optimizer with the positive features of SA such as simplicity of the algorithm and possibility of finding global solution However, annealing process of SA algorithm based on random generator with the zeroth order structural information requires a large of number of iterations highly depending on cooling schedules and stopping criteria. In this paper, MSA algorithm is presented in the form of two phase annealing process with the effective cooling schedule and stopping criteria. With the application to optimal seismic design of steel structures, the performance of the proposed MSA algorithm has been demonstrated with respect to stability and global convergence of the algorithm

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A fully digitized Vector Control of PMSM using 80296SA (80296SA를 이용한 영구자석 동기전동기 벡터제어의 완전 디지털화)

  • 안영식;배정용;이홍희
    • Proceedings of the KIPE Conference
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    • 1998.11a
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    • pp.5-8
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    • 1998
  • The adaptation to vector control theory is so generalized that it is widely used for implementing the high-performance of AC machine. Nowadays, One-Chip microprocessors or DSP chips are being well-used to implement Vector Control algorithm. DSP Chip have less flexibility for memory decoding and I/O rather than One-Chip microprocessor so that is requires more additional circuit and high cost. And the past One-Chip micro processors have difficult of implementation the complex algorithm because of small memory capacity and low arithmetic performance. Therefore we implemented the vector control algorithm of PMSM(Permanent Magnetic Synchronous Motors) using 80296SA form intel , which have many features as 6M memory space, 500MHz clock frequency, including memory decoding circuit and general I/O, Special I/O(EPA, Interrupt controller, Timer/Count, PWM generator) which is proper controller for the complex algorithm or operation program requiring so much memory capacity, So in this paper we fully digitized the vector control of PMSM included SVPWM Voltage controller using the intel 80296SA

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Design of System for Avoiding Identical-Data Upload using SA Hash Algorithm (SA 해쉬 알고리즘을 이용한 동일 데이터 업로드 방지 시스템 설계)

  • Hwang, Sung-Min;Seok, Ho-Jun;Kim, Seog-Gyu
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2011.06a
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    • pp.17-19
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    • 2011
  • 본 논문은 클라이언트에서 서버로 파일을 전송할 때, 클라이언트가 보내고자 하는 파일이 서버에 동일한 파일로 있다면 업로드를 받지 않고, 서버의 파일을 재사용함으로써 트래픽을 감소시킬 수 있을뿐더러, 스토리지 용량 또한 절약할 수 있는 시스템 설계이다. 본 논문에서 제안하는 해쉬(Hash) 함수 SA를 사용하여 파일에 해쉬 코드를 생성함으로써 다른 해쉬 함수 보다 키 값의 길이가 길어지고 빠른 속도로 해쉬 값을 얻을 수가 있다. SA Hash Algorithm을 통해 얻어진 해쉬 값을 서버로 전송하여 서버에 동일한 파일이 있다면 클라이언트에서 파일을 전송 받지 않고, 서버 내부의 파일을 사용하는 것으로 자원 절감 효과를 낼 수 있다. 서버에서의 파일 관리도 기존의 날짜, 아이디 등 구별 방식이 아닌 SA Hash Algorithm으로 생성된 해쉬 값으로 파일을 관리 할 수 있음으로 파일 관리의 편의성뿐만이 아니라 빠른 속도로 파일을 접근할 수 있다.

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On-line Vector Quantizer Design Using Simulated Annealing Method (Simulated Annealing 방법을 이용한 온라인 벡터 양자화기 설계)

  • Song, Geun-Bae;Lee, Haeng-Se
    • The KIPS Transactions:PartB
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    • v.8B no.4
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    • pp.343-350
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    • 2001
  • 백터 양자화기 설계는 다차원의 목적함수를 최소화하는 학습 알고리즘을 필요로 한다. 일반화된 Lloyd 방법(GLA)은 벡터 양자화기 설계를 위해 오늘날 가장 널리 사용되는 알고리즘이다. GLA 는 일괄처리(batch) 방식으로 코드북을 생성하며 목적함수를 단조 감소시키는 강하법(descent algorithm)의 일종이다. 한편 Kohonen 학습법(KLA)은 학습벡터가 입력되는 동안 코드북이 갱신되는 온라인 벡터 양자화기 설계 알고리즘 이다. KLA는 원래 신경망 학습을 위해 Kohonen에 의해 제안되었다. KLA 역시 GLA와 마찬가지로 강하법의 일종이라 할 수 있다. 따라서 이들 두 알고리즘은, 비록 사용하기 편리하고 안정적으로 동작을 하지만, 극소(local minimum) 점으로 수렴하는 문제를 안고 있다. 우리는 이 문제와 관련하여 simulated annealing(SA) 방법의 응용을 논하고자 한다. SA는 현재까지 극소에 빠지지 않고 최소(global minimum)로 수렴하면서, 해의 수렴이 (통계적으로) 보장되는 유일한 방법이라 할 수 있다. 우리는 먼저 GLA에 SA를 응용한 그 동안의 연구를 개괄한다. 다음으로 온라인 방식의 벡터 양자화가 설계에 SA 방법을 응용함으로써 SA 방법에 기초한 새로운 온라인 학습 알고리즘을 제안한다. 우리는 이 알고리즘을 OLVQ-SA 알고리즘이라 부르기로 한다. 가우스-마코프 소스와 음성데이터에 대한 벡터양자화 실험 결과 제안된 방법이 KLA 보다 일관되게 우수한 코드북을 생성함을 보인다.

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An Enhanced Simulated Annealing Algorithm for Rural Postman Problems (Rural Postman Problem 해법을 위한 향상된 Simulated Annealing 알고리즘)

  • 강명주
    • Journal of the Korea Society of Computer and Information
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    • v.6 no.1
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    • pp.25-30
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    • 2001
  • This paper proposes an enhanced Simulated Annealing(SA) algorithm for Rural Postman Problems(RPPs). In SA, the cooling schedule is an important factor for SA algorithms. Hence, in this paper a cooling schedule is proposed for SA for RPPs. In the simulation. the results of the SA using the proposed cooling schedule and the results of the SA using the existing cooling schedules are compared and analyzed. In the simulation results, the proposed method obtained the better results than the existing methods.

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SA-selection-based Genetic Algorithm for the Design of Fuzzy Controller

  • Han Chang-Wook;Park Jung-Il
    • International Journal of Control, Automation, and Systems
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    • v.3 no.2
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    • pp.236-243
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    • 2005
  • This paper presents a new stochastic approach for solving combinatorial optimization problems by using a new selection method, i.e. SA-selection, in genetic algorithm (GA). This approach combines GA with simulated annealing (SA) to improve the performance of GA. GA and SA have complementary strengths and weaknesses. While GA explores the search space by means of population of search points, it suffers from poor convergence properties. SA, by contrast, has good convergence properties, but it cannot explore the search space by means of population. However, SA does employ a completely local selection strategy where the current candidate and the new modification are evaluated and compared. To verify the effectiveness of the proposed method, the optimization of a fuzzy controller for balancing an inverted pendulum on a cart is considered.

Performance Evaluation and Parametric Study of MGA in the Solution of Mathematical Optimization Problems (수학적 최적화 문제를 이용한 MGA의 성능평가 및 매개변수 연구)

  • Cho, Hyun-Man;Lee, Hyun-Jin;Ryu, Yeon-Sun;Kim, Jeong-Tae;Na, Won-Bae;Lim, Dong-Joo
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2008.04a
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    • pp.416-421
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    • 2008
  • A Metropolis genetic algorithm (MGA) is a newly-developed hybrid algorithm combining simple genetic algorithm (SGA) and simulated annealing (SA). In the algorithm, favorable features of Metropolis criterion of SA are incorporated in the reproduction operations of SGA. This way, MGA alleviates the disadvantages of finding imprecise solution in SGA and time-consuming computation in SA. It has been successfully applied and the efficiency has been verified for the practical structural design optimization. However, applicability of MGA for the wider range of problems should be rigorously proved through the solution of mathematical optimization problems. Thus, performances of MGA for the typical mathematical problems are investigated and compared with those of conventional algorithms such as SGA, micro genetic algorithm (${\mu}GA$), and SA. And, for better application of MGA, the effects of acceptance level are also presented. From numerical Study, it is again verified that MGA is more efficient and robust than SA, SGA and ${\mu}GA$ in the solution of mathematical optimization problems having various features.

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