• Korean Management Science Review
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• v.15 no.2
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• pp.153-159
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• 1998

Clustering or classification is a very fundamental task that may occur almost everywhere for the purpose of grouping. Optimal clustering is an example of very complicated combinatorial optimization problem and it is hard to develop a generally applicable optimal algorithm. In this paper we propose a general-purpose algorithm for the optimal clustering based on SA(simulated annealing). Among various iterative global optimization techniques imitating natural phenomena that have been proposed and utilized successfully for various combinatorial optimization problem, simulated annealing has its superiority because of its convergence property and simplicity. We first present a version of accelerated simulated annealing(ASA) and then we apply ASA to develop an efficient clustering algorithm. Application examples are also given.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.12
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• pp.589-594
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• 2000

The fuzzy controllers have been applied to the power system stabilizer due to its excellent properties on the nonlinear systems. But the design process of fuzzy controller requires empirical and heuristic knowledge of human experts as well as many trial-and-errors in general. This process is time consuming task. This paper presents an parameters tuning method of the fuzzy power system stabilizer using the genetic algorithm and simulated annealing(SA). The proposed method searches the local minimum point using the simulated annealing algorithm. The proposed method is applied to the one-machine infinite-bus of a power system. Through the comparative simulation with conventional stabilizer and fuzzy stabilizer tuned by genetic algorithm under various operating conditions and system parameters, the robustness of fuzzy stabilizer tuned by proposed method with respect to the nonlinear power system is verified.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.87-92
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• 2002

Placement is an important step in the physical design of VLSI circuits. It is the problem of placing a set of circuit modules on a chip to optimize the circuit performance. The most popular algorithms for placement include the cluster growth, simulated annealing and integer linear programming. In this paper we propose a stochastic evolution algorithm searching solution space for the placement problem, and then compare it with simulated annealing by analyzing the results of each implementation.

• Journal of Ocean Engineering and Technology
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• v.16 no.4
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• pp.25-31
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• 2002

This paper is to find optimum design of plane framed structures with discrete variables. Global search algorithms for this problem are Genetic Algorithms(GAs), Simulated Annealing(SA) and Shuffled Complex Evolution(SCE), and hybrid methods (GAs-SA, GAs-SCE). GAs and SA are heuristic search algorithms and effective tools which is finding global solution for discrete optimization. In particular, GAs is known as the search method to find global optimum or near global optimum. In this paper, reinforced concrete plane frames with rectangular section and steel plane frames with W-sections are used for the design of discrete optimization. These structures are designed for stress constraints. The robust and effectiveness of Genetic Algorithms are demonstrated through several examples.

• Journal of Information Processing Systems
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• v.18 no.5
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• pp.665-676
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• 2022

In modern logistics, the effective use of the vehicle volume and loading capacity will reduce the logistic cost. Many heuristic algorithms can solve this knapsack problem, but lots of these algorithms have a drawback, that is, they often fall into locally optimal solutions. A fusion optimization method based on simulated annealing algorithm (SA) and binary particle swarm optimization algorithm (BPSO) is proposed in the paper. We establish a logistics knapsack model of the fusion optimization algorithm. Then, a new model of express logistics simulation system is used for comparing three algorithms. The experiment verifies the effectiveness of the algorithm proposed in this paper. The experimental results show that the use of BPSO-SA algorithm can improve the utilization rate and the load rate of logistics distribution vehicles. So, the number of vehicles used for distribution and the average driving distance will be reduced. The purposes of the logistics knapsack problem optimization are achieved.

• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.349-356
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• 2004

In this paper, a practical image security system using SA algorithm and 4-f optical correlator system is proposed. The encrypted image and key image with binary phase components are generated using an iterative SA algorithm. a decrypted image is found through the correlation of the encrypted and key images using 4-f optical correlator system. The encrypted and key images are consisted of binary phase components. So, it is easy to implement the optical security system using the proposed technique. And if we fix the encrypted image in the optical security system and change the key images, we get different images, so it is possible to apply to the distinguished authorization system using different key images. Computer simulations show that despite the binary phase components of the two images(encrypted and key image), decrypted images are generated.

• Journal of the Korea Society of Computer and Information
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• v.18 no.12
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• pp.197-205
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• 2013

In this study, we developed a program of optimizing stand-level carbon stock using a stand-level yield model and the Simulated Annealing (SA) heuristic method to derive a optimized forest treatment solution. The SA is one of the heuristic algorithms that can provide a desirable management solution when dealing with various management purposes. The SA heuristic algorithm applied 'thermal equilibrium test', a thresholds approach to solve the phenomenon that does not find an optimum solution and stays at a local optimum value during the process. We conducted a sensitivity test for the temperature reduction rate, the major parameter of the thermal equilibrium test, to analyze its influence on the objective function value and the total iteration of the optimization process. Using the developed program, three scenarios were compared: a common treatment in forestry (baseline), the optimized solution of maximizing the amount of harvest(alternative 1), and the optimized solution of maximizing the amount of carbon stocks(alternative 2). As the results, we found that the alternative 1 showed provide acceptable solutions for the objectives. From the sensitivity test, we found that the objective function value and the total iteration of the process can be significantly influenced by the temperature reduction rate. The developed program will be practically used for optimizing stand-level carbon stock and developing optimized treatment solutions.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.8
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• pp.1545-1551
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• 2002

The optical storage device has recently experienced significant improvement, especially for the aspects of high capacity and fast transfer rate. However, it is necessary to study a new shape of air bearing surface for the rotary type actuator because the optical storage device has the lower access time than that of HDD (Hard Disk Drives). In this study, we proposed the air bearing shape by using SA (Simulated Annealing) algorithm which is very effective to achieve the global optimum instead of many local optimums. The objective of optimization is to minimize the deviation in flying height from a target value 100nm. In addition, the pitch and roll angle should be maintained within the operation limits.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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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.

• Structural Engineering and Mechanics
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• v.35 no.1
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• pp.19-35
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• 2010

This paper proposes a hybrid heuristic and criteria-based method of optimum design which combines the advantages of both the iterated simulated annealing (SA) algorithm and the rigorously derived optimality criteria (OC) for structural optimum design of reinforced concrete (RC) buildings under multi-load cases based on the current Chinese design codes. The entire optimum design procedure is divided into two parts: strength optimum design and stiffness optimum design. A modified SA with the strategy of adaptive feasible region is proposed to perform the discrete optimization of RC frame structures under the strength constraints. The optimum stiffness design is conducted using OC method with the optimum results of strength optimum design as the lower bounds of member size. The proposed method is integrated into the commercial software packages for building structural design, SATWE, and for finite element analysis, ANSYS, for practical applications. Finally, two practical frame-shear-wall structures (15-story and 30-story) are optimized to illustrate the effectiveness and practicality of the proposed optimum design method.