• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.598-603
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• 2008

Sequence-Pair(SP)는 플로어플랜을 표현하는 모델 중 하나로써, 일반적으로 SP 모델을 사용하는 플로 어프래너 (floorplanner)는 Simulated-Annealing (SA) 알고리즙을 통해 해 탐색 과정을 수행한다. SP 모델을 이용한 다양한 논문에서 플로어플랜 성능 향상을 위해 평가함수의 개선과 스케줄링 기법 향상을 모색하였으며, 평가함수의 경우 O(nlogn) 시간 알고리즘이 존재한다. 본 논문에서는 SP 모델을 이용한 SA 기법에서 SA의 해 탐색 과정 중 초기 해 탐색 시점에서 좋은 해를 빠르게 찾을 수 있는 방법을 제안한다. 제안 기법은 기존의 SA 프레임펙을 수정한 2단계 SA 알고리즘으로써 SP에 대응하는 배치를 압축하고 압축한 배치를 역변환하는 과정으로 구성된다. 실험과 결과를 통해 제안기법의 효과를 보이며, 평균적으로 동일한 SA 환경 하에서 제안기법이 최종결과 면에서 우수함을 보인다.

• Structural Engineering and Mechanics
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• v.25 no.2
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• pp.239-268
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• 2007

This paper deals with optimal stacking sequence design of laminate composite structures. The stacking sequence optimisation of laminate composites is formulated as a combinatorial problem and is solved using Simulated Annealing (SA), an algorithm devised based on inspiration of physical process of annealing of solids. The combinatorial constraints are handled using a correction strategy. The SA algorithm is strengthened by embedding Tabu search in order to prevent recycling of recently visited solutions and the resulting algorithm is referred to as tabu embedded simulated Annealing (TSA) algorithm. Computational performance of the proposed TSA algorithm is enhanced through cache-fetch implementation. Numerical experiments have been conducted by considering rectangular composite panels and composite cylindrical shell with different ply numbers and orientations. Numerical studies indicate that the TSA algorithm is quite effective in providing practical designs for lay-up sequence optimisation of laminate composites. The effect of various neighbourhood search algorithms on the convergence characteristics of TSA algorithm is investigated. The sensitiveness of the proposed optimisation algorithm for various parameter settings in simulated annealing is explored through parametric studies. Later, the TSA algorithm is employed for multi-criteria optimisation of hybrid composite cylinders for simultaneously optimising cost as well as weight with constraint on buckling load. The two objectives are initially considered individually and later collectively to solve as a multi-criteria optimisation problem. Finally, the computational efficiency of the TSA based stacking sequence optimisation algorithm has been compared with the genetic algorithm and found to be superior in performance.

• Journal of Internet Computing and Services
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• v.6 no.6
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• pp.99-106
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• 2005

The task scheduling in multiprocessor system Is one of the key elements in the effective utilization of multiprocessor systems. The optimal assignment of tasks to multiprocessor is, in almost all practical cases, an NP hard problem. Consequently various modern heuristics based algorithms have been proposed for practical reason. Recently, several approaches using Genetic Algorithm (GA) are proposed. However, these algorithms have only one objective such as minimizing cost and makespan. This paper proposes a new task scheduling algorithm using Genetic Algorithm combined simulated annealing (GA+SA) on multiprocessor environment. In solution algorithms, the Genetic Algorithm (GA) and the simulated annealing (SA) are cooperatively used. In this method. the convergence of GA is improved by introducing the probability of SA as the criterion for acceptance of new trial solution. The objective of proposed scheduling algorithm is to minimize makespan and total number of processors used. The effectiveness of the proposed algorithm is shown through simulation studies. In simulation studies, the results of proposed algorithm show better than that of other algorithms.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.1 s.71
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• pp.27-37
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• 2006

A Metropolis genetic algorithm (MGA) is developed and applied for the structural design optimization. In MGA, favorable features of Metropolis criterion of simulated annealing (SA) are incorporated in the reproduction operations of simple genetic algorithm (SGA). This way, the MGA maintains the wide varieties of individuals and preserves the potential genetic information of early generations. Consequently, the proposed MGA alleviates the disadvantages of premature convergence to a local optimum in SGA and time consuming computation for the precise global optimum in SA. Performances and applicability of MGA are compared with those of conventional algorithms such as Holland's SGA, Krishnakumar's micro GA, and Kirkpatrick's SA. Typical numerical examples are used to evaluate the computational performances, the favorable features and applicability of MGA. The effects of population sizes and maximum generations are also evaluated for the performance reliability and robustness of MGA. From the theoretical evaluation and numerical experience, it is concluded that the proposed MGA Is a reliable and efficient tool for structural design optimization.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.256-256
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• 2000

In this parer, we present a real-time path planning algorithm which is integrated the artificial potential field(APF) and simulated annealing(SA) methods for mobile robot. The APF method in path planning has gained popularity since 1990's. It doesn't need the modeling of the complex configuration space of robot, and is easy to apply the path planning with simple computation. However, there is a major problem with APF method. It is the formation of local minima that can trap the robot before reaching its goal. So, to provide local minima recovery, we apply the SA method. The effectiveness of the proposed algorithm is verified through simulation.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.322-333
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• 2012

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability. For this reason, Radar Resource Management(RRM) becomes new challenging issue. RRM is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed a rule-based scheduling algorithm and Simulated Annealing(SA) based scheduling algorithm, which are alternatively selected and applied to beam scheduler according radar load status in real-time. The performance of the proposed algorithm was evaluated on the multi-function radar scenario. As a result, we showed that our proposed algorithm can process a lot of beams at the right time with real time capability, compared with applying only rule-based scheduling algorithm. Additionally, we showed that the proposed algorithm can save scheduling time remarkably, compared with applying only SA-based scheduling algorithm.

• IE interfaces
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• v.15 no.2
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• pp.189-198
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• 2002

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.90-93
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• 2000

This paper presents job scheduling for non-identical parallel machines using Simulated Annealing (SA). The scheduling problem accounts for allotting work parts of L lots into M parallel machines, where each lot is composed of N homogeneous jobs. Some lots may have different jobs while every job within each lot has common due date. Each machine has its own performance and set up time according to the features of the machine, and also by job types. A meta-heuristic, SA, is applied in this study to determine the job sequences of the scheduling problem so as to minimize total tardiness of due. The SA method is compared with a conventional steepest descent(SD) algorithm that is a typical tool for finding local optimum. The comparison shows the SA is much better than the SD in terms tardiness while SA takes longer , but acceptable time.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.439-442
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• 2003

In order to solve the difficulties of parameter settings in SA algorithm, an improved practical SA algorithm is proposed by employing the threading techniques, appropriate software structures, and dynamic adjustments of temperature parameters. Threads provide a mechanism to realize a parallel processing under a disperse environment by controlling the flux of internal information of an application. Thread services divide a process by multiple processes leading to parallel processing of information to access common data. Therefore, efficient search is achieved by multiple search processes, different initial conditions, and automatic temperature adjustments. The proposed are methods are evaluated, for three types of Traveling Salesman Problem (TSP) (random-tour, fractal-tour, and TSPLIB test data)are used for the performance evaluation. The experimental results show that the computational time is 5％ decreased comparing to conventional SA algorithm, furthermore there is no need for manual parameter settings. These results also demonstrate that the proposed method is applicable to real-world vehicle routing problems.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.5
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• pp.27-36
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• 2001

This paper proposes new design algorithms based on stochastic relaxation (SR) for an on-line vector quantizer (VQ) design. These proposed SR methods solve the local entrapment problems of the conventional Kohonen learning algorithm (KLA). These SR methods cover two different types depending upon the use of simulated annealing (SA) : the one that uses SA is called the OLVQ SA and the other the OLVQ SR. These methods arc combined with the KLA and therefore preserve the its convergence properties. Experimental results for Gauss Markov sources, real speech and image demonstrate that the proposed algorithms can consistently provide better codebooks than the KLA.