• IE interfaces
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• v.17 no.spc
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• pp.69-78
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• 2004

This paper presents a simulated algorithm(SA) for the optimal reliability design problem of a series system with multiple component choices incorporated at each subsystem. The objective of the problem is to maximize the system reliability while satisfying some constraint on system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. The SA algorithm is developed by introducing some solution-improvements methods. Numerical examples are tested and the results are compared. The results have demonstrated the efficiency and the effectiveness of the proposed SA algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.105-114
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• 2000

Job Shop Problem which consists of the m different machines and n jobs is a NP-hard problem of the combinatorial optimization. Each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. Each machine can process at most one operation at a time. The purpose of this paper is to develop the heuristic method to solve large scale scheduling problem using Constraint Satisfaction Problem method and Simulated Annealing. The proposed heuristic method consists of the search algorithm and optimization algorithm. The search algorithm is to find the solution in the solution space using CSP concept such as backtracking and domain reduction. The optimization algorithm is to search the optimal solution using SA. This method is applied to MT06, MT10 and MT20 Job Shop Problem, and compared with other heuristic method.

• IE interfaces
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• v.12 no.1
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• pp.94-101
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• 1999

The set covering(SC) problem is the problem of covering all the rows of an $m{\times}n$ matrix of ones and zeros by a subset of columns with a minimal cost. It has many practical applications of modeling of real world problems. The SC problem has been proven to be NP-complete and many algorithms have been presented to solve the SC problem. In this paper we present hybrid simulated annealing(HSA) algorithm based on the Simulated Annealing(SA) for the SC problem. The HSA is an algorithm which combines SA with a crossover operation in a genetic algorithm and a local search method. Our experimental results show that the HSA obtains better results than SA does.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.843-859
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• 2024

The university course scheduling problem (UCSP) aims at optimally arranging courses to corresponding rooms, faculties, students, and timeslots with constraints. Previously, the university staff solved this thorny problem by hand, which is very time-consuming and makes it easy to fall into chaos. Even some meta-heuristic algorithms are proposed to solve UCSP automatically, while most only utilize one single algorithm, so the scheduling results still need improvement. Besides, they lack an in-depth analysis of the inner algorithms. Therefore, this paper presents a novel and practical approach based on Tabu search and simulated annealing algorithms for solving USCP. Firstly, the initial solution of the UCSP instance is generated by one construction heuristic algorithm, the first fit algorithm. Secondly, we defined one union move selector to control the moves and provide diverse solutions from initial solutions, consisting of two changing move selectors. Thirdly, Tabu search and simulated annealing (SA) are combined to filter out unacceptable moves in a parallel mode. Then, the acceptable moves are selected by one adaptive decision algorithm, which is used as the next step to construct the final solving path. Benefits from the excellent design of the union move selector, parallel tabu search and SA, and adaptive decision algorithm, the proposed method could effectively solve UCSP since it fully uses Tabu and SA. We designed and tested the proposed algorithm in one real-world (PKNU-UCSP) and ten random UCSP instances. The experimental results confirmed its effectiveness. Besides, the in-depth analysis confirmed each component's effectiveness for solving UCSP.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.7 s.110
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• pp.684-693
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• 2006

In this paper, the SA (Specific Absorption) distribution in a human head, exposed to wideband pulse EMF, has been analyzed by taking into account the dispersion characteristics of biological tissues. The dispersive properties of biological tissues are characterized by the 4th Cole-Cole model. Currently, there is no dispersive FDTD algorithm to implement the 4th Cole-Cole model accurately. Thus, in this paper the FDTD methods with the dispersive algorithm for the 1st-order Cole-Cole model and the 3rd-order Debye model were used for SA analysis. The validity of each model has been investigated first, and then the effects of dispersion on SA distribution have been studied.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.89-95
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• 2002

Global routing is to assign each net to routing regions to accomplish the required interconnections. The most popular algorithms for global routing inlcude maze routing algorithm, line-probe algorithm, shortest path based algorithm, and Steiner tree based algorithm. In this paper we propose weighted network heuristic(WNH) as a minimal Steiner tree search method in a routing graph and a genetic algorithm based on WNH for the global routing. We compare the genetic algorithm(GA) with simulated annealing(SA) by analyzing the results of each implementation.

• Journal of Korean Society of Steel Construction
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• v.27 no.2
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• pp.131-142
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• 2015

In this paper, we present an optimization of truss structures subjected to stress, buckling, and natural frequency constraints. The main objective of the present study is to propose an efficient HA-SA algorithm for solving the truss optimization subject to multiple constraints. The procedure of hybrid HA-SA is a search method which a design values in harmony memory of harmony search are used as an initial value designs in simulated annealing search method. The efficient optimization of HA-SA is illustrated through several optimization examples. The examples of truss structures are used 10-Bar truss, 52-Bar truss (Dome), and 72-Bar truss for natural frequency constraints, and used 18-Bar truss and 47-Bar (Tower) truss for stress and buckling constraints. The optimum results are compared to those of different techniques. The numerical results are demonstrated the advantages of the HA-SA algorithm in truss optimization with multiple constraints.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2414-2421
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• 1999

This paper proposes two kinds of heuristic algorithms for Rural Postman Problems(RPPs). One is a Simulated Annealing (SA) algorithm for RPPs. In SA, we propose a new cooling schedule which affects the performance of SA. The other is a Genetic Algorithm(GA) for RPPs. In GA, we propose a chromosome structure for RPPs which are edge-oriented problems. In simulations, we compared the proposed methods with the existing methods and the results show that the proposed methods produced better results than the existing methods.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.520-525
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• 2003

The determination of unknown parameters in rotating machinery is a difficult task and optimization techniques represent an alternative technique for parameter identification. The Simulated Annealing(SA) and Genetic Algorithm(GA) are powerful global optimization algorithm. This paper proposes new hybrid algorithm which combined GA with SA and local search algorithm for the purpose of parameter identification. Numerical examples are also presented to verify the efficiency of proposed algorithm. And, this paper presents the general methodology based on hybrid algorithm to identify unknown bearing parameters of flexible rotors using measured unbalance responses. Numerical examples are used to ilustrate the methodology used, which is then validated experimentally.

• Journal of Satellite, Information and Communications
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• v.8 no.4
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• pp.130-134
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• 2013

This paper describes the basic principles of 3D broadcast system and proposes new 3D broadcast technology that reduce the amount of data by applying CS(Compressed Sensing). Differences between Sampling theory and the CS technology concept was described. Recently proposed CS algorithm AMP(Approximate Message Passing) and CoSaMP(Compressive Sampling Matched Pursuit) was described. Image data that compressed and restored by these algorithm was compared. Calculation time of the algorithm having a low complexity is determined.