• 제목/요약/키워드: Simulated Algorithm

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Simulated Annealing의 가속화와 ATM 망에서의 가상경로 설정에의 적용 (Acceleration of Simulated Annealing and Its Application for Virtual Path Management in ATM Networks)

  • 윤복식;조계연
    • 한국경영과학회지
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    • 제21권2호
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    • pp.125-140
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    • 1996
  • Simulated annealing (SA) is a very promising general purpose algorithm which can be conveniently utilized for various complicated combinatorial optimization problems. But its slowness has been pointed as a major drawback. In this paper, we propose an accelerated SA and test its performance experimentally by applying it for two standard combinatorial optimization problems (TSP(Travelling Salesman Problem) and GPP(Graph Partitioning Problem) of various sizes. It turns out that performance of the proposed method is consistently better both in convergenge speed and the quality of solution than the conventional SA or SE (Stochastic Evolution). In the second part of the paper we apply the accelerated SA to solve the virtual path management problem encountered in ATM netowrks. The problem is modeled as a combinatorial optimization problem to optimize the utilizy of links and an efficient SA implementation scheme is proposed. Two application examples are given to demonstrate the validity of the proposed algorithm.

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매입형 영구자석 동기전동기의 최적설계를 위한 시뮬레이티드 애닐링과 결정론적 탐색법의 혼합적용 (An Application of Simulated Annealing Combining Deterministic Search to Optimal Design of Interior Permanent Magnet Synchronous Motors)

  • 심동준;정현교;한송엽;원종수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1994년도 하계학술대회 논문집 A
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    • pp.159-161
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    • 1994
  • This paper presents a combined algorithm of simulated annealing and determinstic method which overcomes the defects of two methods and guarantees the fast convergence to the global optimum. This optimization method is applied to optimal design of Interior Permanent Magnet Synchronous Motor. And the result of the proposed algorithm is compared with that of simulated annealing alone.

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Location Analysis for Emergency Medical Service Vehicle in Sub District Area

  • Nanthasamroeng, Natthapong
    • Industrial Engineering and Management Systems
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    • 제11권4호
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    • pp.339-345
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    • 2012
  • This research aims to formulate a mathematical model and develop an algorithm for solving a location problem in emergency medical service vehicle parking. To find an optimal parking location which has the least risk score or risk priority number calculated from severity, occurrence, detection, and distance from parking location for emergency patients, data were collected from Pratoom sub-district Disaster Prevention and Mitigation Center from October 2010 to April 2011. The criteria of risk evaluation were modified from Automotive Industry Action Group's criteria. An adaptive simulated annealing algorithm with multiple cooling schedules called multi-agent simulated quenching (MASQ) is proposed for solving the problem in two schemes of algorithms including dual agent and triple agent quenching. The result showed that the solution obtained from both scheme of MASQ was better than the traditional solution. The best locations obtained from MASQ-dual agent quenching scheme was nodes #5 and #133. The risk score was reduced 61% from 6,022 to 2,371 points.

Hatch를 고려한 컨테이너 터미널 적재순서 최적화 연구 (A Study on the Optimization of Stowage Planning for Container Terminal Considered by Hatch)

  • 이상헌;김문규;안태호
    • 산업공학
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    • 제19권4호
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    • pp.270-280
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    • 2006
  • The shipping plan for an efficient augmentation of terminal is NP-hard problem which is subordinate to a shipping quantity. The load location problem and stowage planning problem are two important tactical problems for the efficient operations of container terminals. This paper is concerned with reduction of feasible region in constraints for stowage planning. After designing model which minimizes the number of shifting and the travel distance of the transfer crane, the simulated annealing algorithm is employed to search optimal solution quickly and accurately. In order to apply more realistic approach, the partial restriction through adding hatch is complemented to stowage planning decision problem applied in cluster. A variety of numerical experiments demonstrated that solutions by simulated annealing algorithm are useful and applicable in practice.

화물컨테이너 운송을 위한 시뮬레이티드 어닐링 기반의 차량경로계획 (Simulated Annealing Based Vehicle Routing Planning for Freight Container Transportation)

  • 이상헌;최해정
    • 산업공학
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    • 제20권2호
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    • pp.204-215
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    • 2007
  • This paper addresses vehicle routing planning in freight container transportation systems where a number of loaded containers are to be delivered to their destination places. The system under consideration is static in that all transportation requirements are predetermined at the beginning of a planning horizon. A two-phased procedure is presented for freight container transportation. In the first phase, the optimal model is presented to determine optimal total time to perform given transportation requirements and the minimum of number of vehicles required. Based on the results from the optimal model, in the second phase, ASA(Accelerated Simulated Annealing) algorithm is presented to perform all transportation requirements with the least number of vehicles by improving initial vehicle routing planning constructed by greedy method. It is found that ASA algorithm has an excellent global searching ability through various experiments in comparison with existing methods.

담금질을 사용한 비계량 다차원 척도법 (Non-Metric Multidimensional Scaling using Simulated Annealing)

  • 이창용;이동주
    • 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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    • 제16권6호
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    • pp.648-653
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    • 2010
  • 비계량 다차원 척도법은 개체들 간의 비유사성이 비계량으로 주어져 개체들 간의 거리 개념을 설정하기 어려운 경우에 개체들을 유클리드 공간 상으로 사상하여 개체 간의 관련성을 연구하는 방법으로 지역 최적치가 많은 최적화 문제로 간주할 수 있다. 비계량 다차원 척도법을 위한 기존의 알고리즘은 최대 경사법을 사용함으로 일단 지역 최적치에 도달하면 더 이상 향상된 해를 찾기 어렵다는 단점이 있다. 이러한 단점을 해결하기 위하여 본 논문에서는 담금질 방법을 비계량 다차원 척도법에 접목하여 지역 최적치에 빠지지 않고 전역 최적치를 효율적으로 찾을 수 있는 새로운 비계량 다차원 척도법 알고리즘을 제안하였다. 제안한 알고리즘을 벤치마킹 문제에 적용하고 실험을 통하여 기존 알고리즘과 비교 분석한 결과, 제안한 알고리즘은 기존 알고리즘 대비 0.7%에서 3.2%의 향상률을 보였다. 또한 통계적 가설 검정을 통하여 제안한 알고리즘의 우수성을 입증하였다.

Development of a Modified Random Signal-based Learning using Simulated Annealing

  • Han, Chang-Wook;Lee, Yeunghak
    • Journal of Multimedia Information System
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    • 제2권1호
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    • pp.179-186
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    • 2015
  • This paper describes the application of a simulated annealing to a random signal-based learning. The simulated annealing is used to generate the reinforcement signal which is used in the random signal-based learning. Random signal-based learning is similar to the reinforcement learning of neural network. It is poor at hill-climbing, whereas simulated annealing has an ability of probabilistic hill-climbing. Therefore, hybridizing a random signal-based learning with the simulated annealing can produce better performance than before. The validity of the proposed algorithm is confirmed by applying it to two different examples. One is finding the minimum of the nonlinear function. And the other is the optimization of fuzzy control rules using inverted pendulum.

A Hybrid Metaheuristic for the Series-parallel Redundancy Allocation Problem in Electronic Systems of the Ship

  • Son, Joo-Young;Kim, Jae-Hwan
    • Journal of Advanced Marine Engineering and Technology
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    • 제35권3호
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    • pp.341-347
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    • 2011
  • The redundancy allocation problem (RAP) is a famous NP.complete problem that has beenstudied in the system reliability area of ships and airplanes. Recently meta-heuristic techniques have been applied in this topic, for example, genetic algorithms, simulated annealing and tabu search. In particular, tabu search (TS) has emerged as an efficient algorithmic approach for the series-parallel RAP. However, the quality of solutions found by TS depends on the initial solution. As a robust and efficient methodology for the series-parallel RAP, the hybrid metaheuristic (TSA) that is a interactive procedure between the TS and SA (simulated annealing) is developed in this paper. In the proposed algorithm, SA is used to find the diversified promising solutions so that TS can re-intensify search for the solutions obtained by the SA. We test the proposed TSA by the existing problems and compare it with the SA and TS algorithm. Computational results show that the TSA algorithm finds the global optimal solutions for all cases and outperforms the existing TS and SA in cases of 42 and 56 subsystems.

유전자 알고리즘을 이용한 장·단기 유출모형의 매개변수 최적화 (Parameter Optimization of Long and Short Term Runoff Models Using Genetic Algorithm)

  • 김선주;지용근;김필식
    • 한국농공학회논문집
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    • 제46권5호
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    • pp.41-52
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    • 2004
  • In this study, parameters of long and short term runoff model were optimized using genetic algorithm as a basic research for integrated water management in a watershed. In case of Korea where drought and flood occurr frequently, the integrated water management is necessary to minimize possible damage of drought and flood. Modified TANK model was optimized as a long term runoff model and storage-function model was optimized as a short term runoff model. Besides distinguished parameters were applied to modified TANK model for supplementing defect that the model estimates less runoff in the storm period. As a result of application, simulated long and short term runoff results showed 7% and 5% improvement compared with before optimized on the average. In case of modified TANK model using distinguished parameters, the simulated runoff after optimized showed more interrelationship than before optimized. Therefore, modified TANK model can be applied for the long term water balance as an integrated water management in a watershed. In case of storage-function model, simulated runoff in the storm period showed high interrelationship with observed one. These optimized models can be applied for the runoff analysis of watershed.

시뮬레이티드 어닐링을 이용한(m, n)중 연속(r,s) : F 시스템의 정비모형 (A Maintenance Design of Connected-(r, s)-out-of-(m, n) F System Using Simulated Annealing)

  • 이상헌;강영태;신동열
    • 대한산업공학회지
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    • 제34권1호
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    • pp.98-107
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    • 2008
  • The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unittime. This study considers a linear connected-(r, s)-ouI-of-(m, n):f lattice system whose components are orderedlike the elements of a linear (m, n)-matrix. We assume that all components are in the state 1 (operating) or 0(failed) and identical and s-independent. The system fails whenever at least one connected (r, s)-submatrix offailed components occurs. To find the optimal threshold of maintenance intervention, we use a simulatedannealing(SA) algorithm for the cost optimization procedure. The expected cost per unit time is obtained byMonte Carlo simulation. We also has made sensitivity analysis to the different cost parameters. In this study,utility maintenance model is constructed so that minimize the expense under full equipment policy throughcomparison for the full equipment policy and preventive maintenance policy. The full equipment cycle and unitcost rate are acquired by simulated annealing algorithm. The SA algorithm is appeared to converge fast inmulti-component system that is suitable to optimization decision problem.