• 한국경영과학회지
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• 제29권3호
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• pp.145-155
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• 2004

The design of a communication network has long been a challenging optimization problem. Since the optimal design of a network topology is a well known as a NP-complete problem, many researches have been conducted to obtain near optimal solutions in polynomial time instead of exact optimal solutions. All of these researches suggested diverse heuristic algorithms that can be applied to network design problems. Among these algorithms, a simulated annealing algorithm has been proved to guarantee a good solution for many NP-complete problems. in applying the simulated annealing algorithms to network design problems, generating mechanisms for initial solutions and candidate solutions play an important role in terms of goodness of a solution and efficiency. This study aims at analyzing these mechanisms through experiments, and then suggesting reliable mechanisms.

• 동력기계공학회지
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• 제8권2호
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• pp.45-52
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• 2004

This paper describes the optimum design for journal bearings by using simulated annealing method. Simulated annealing algorithm is an optimization technique to calculate global and local optimum solutions. Dynamic characteristics of the journal bearing are calculated by using finite difference method (FDM), and these values are used for the procedure of journal bearing optimization. The objective is to minimize the resonance response (Q factor) of the simple rotor system supported by the journal bearings. Bearing clearance and length to diameter ratio are used as the design variables.

• Steel and Composite Structures
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• 제7권3호
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• pp.201-217
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• 2007

Two combinatorial optimization algorithms, tabu search and simulated annealing, are presented for the minimum-weight design of geometrically non-linear steel plane frames. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange (W) shapes. Stress constraints of AISC Load and Resistance Factor Design (LRFD) specification, maximum and interstorey drift constraints and size constraints for columns were imposed on frames. The stress constraints of AISC Allowable Stress Design (ASD) were also mounted in the two algorithms. The comparisons between AISC-LRFD and AISC-ASD specifications were also made while tabu search and simulated annealing were used separately. The algorithms were applied to the optimum design of three frame structures. The designs obtained using tabu search were compared to those where simulated annealing was considered. The comparisons showed that the tabu search algorithm yielded better designs with AISC-LRFD code specification.

• International Journal of CAD/CAM
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• 제12권1호
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• pp.9-19
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• 2012

Generation of optimum planar B-spline curve in terms of minimum deviation and required fairness to approximate a target shape defined by a strip-shaped unorganized 2D point cloud is studied. It is proposed to use the location of control points as variables within the geometric optimization framework of point distance minimization. An adaptive simulated annealing heuristic optimization algorithm is developed to iteratively update an initial approximate curve towards the target shape. The new implementation comprises an adaptive cooling procedure in which the temperature change is adaptively dependent on the objective function evolution. It is shown that the proposed method results in an improved convergence speed when compared to the standard simulated annealing method. A couple of examples are included to show the applicability of the proposed method in the surface model reconstruction directly from point cloud data.

• Journal of Mechanical Science and Technology
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• 제20권8호
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• pp.1125-1138
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• 2006

The optimal design of the squeeze film damper (SFD) for rotor system has been studied in previous researches. However, these researches have not been considering jumping or nonlinear phenomena of a rotor system with SFD. This paper represents an optimization technique for linear and nonlinear response of a simple rotor system with SFDs by using a hybrid GA-SA algorithm which combined enhanced genetic algorithm (GA) with simulated annealing algorithm (SA). The damper design parameters are the radius, length and radial clearance of the damper. The objective function is to minimize the transmitted load between SFD and foundation at the operating and critical speeds of the rotor system with SFD which has linear and nonlinear unbalance responses. The numerical results show that the transmitted load of the SFD is greatly reduced in linear and nonlinear responses for the rotor system.

• 산업경영시스템학회지
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• 제42권1호
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• pp.8-20
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• 2019

The vehicle routing problem is one of the vibrant research problems for half a century. Many studies have extensively studied the vehicle routing problem in order to deal with practical decision-making issues in logistics. However, developments of new logistics strategies have inevitably required investigations on solution methods for solving the problem because of computational complexity and inherent constraints in the problem. For this reason, this paper suggests a simulated annealing (SA) algorithm for a variant of vehicle routing problem introduced by a previous study. The vehicle routing problem is a multi-depot and multi-trip vehicle routing problem with multiple heterogeneous vehicles restricted by the maximum permitted weight and the number of compartments. The SA algorithm generates an initial solution through a greedy-type algorithm and improves it using an enhanced SA procedure with three local search methods. A series of computational experiments are performed to evaluate the performance of the heuristic and several managerial findings are further discussed through scenario analyses. Experiment results show that the proposed SA algorithm can obtain good solutions within a reasonable computation time and scenario analyses show that a transportation system visiting non-dedicated factories shows better performance in truck management in terms of the numbers of vehicles used and trips for serving customer orders than another system visiting only dedicated factories.

• 산업경영시스템학회지
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• 제40권2호
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• pp.92-98
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• 2017

Data clustering determines a group of patterns using similarity measure in a dataset and is one of the most important and difficult technique in data mining. Clustering can be formally considered as a particular kind of NP-hard grouping problem. K-means algorithm which is popular and efficient, is sensitive for initialization and has the possibility to be stuck in local optimum because of hill climbing clustering method. This method is also not computationally feasible in practice, especially for large datasets and large number of clusters. Therefore, we need a robust and efficient clustering algorithm to find the global optimum (not local optimum) especially when much data is collected from many IoT (Internet of Things) devices in these days. The objective of this paper is to propose new Hybrid Simulated Annealing (HSA) which is combined simulated annealing with K-means for non-hierarchical clustering of big data. Simulated annealing (SA) is useful for diversified search in large search space and K-means is useful for converged search in predetermined search space. Our proposed method can balance the intensification and diversification to find the global optimal solution in big data clustering. The performance of HSA is validated using Iris, Wine, Glass, and Vowel UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KSAK (K-means+SA+K-means) and SAK (SA+K-means) are better than KSA(K-means+SA), SA, and K-means in our simulations. Our method has significantly improved accuracy and efficiency to find the global optimal data clustering solution for complex, real time, and costly data mining process.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
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• pp.25-25
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• 1994

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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• pp.360-362
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• 1998

In the original mixtures of experts framework, the parameters of the network are determined by gradient descent, which is naturally slow. In [2], the Expectation-Maximization(EM) algorithm is used instead, to obtain the network parameters, resulting in substantially reduced training times. This paper presents the new EM algorithm for prediction. We show that an Efficient training algorithm may be derived for the HME network. To verify the utility of the algorithm we look at specific examples in time series prediction. The application of the new EM algorithm to time series prediction has been quiet successful.

• 한국통신학회논문지
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• 제29권2C호
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• pp.306-314
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• 2004

배열 안테나를 사용하고 있는 CDMA 기반의 이동 통신 기지국은 효율적인 빔 형성을 위해서 배열 안테나 시스템을 이루고 있는 송수신기 모듈의 정확한 성능을 필요로 하며 이를 위해 오차 보정이 반드시 필요하다. 일반적으로 오차 보정은 internal 오차 보정과 external 오차 보정으로 크게 구분 할 수 있다. 특히 internal 오차 보정은 수신기 모듈을 이루고 있는 RF/IF 회로 소자들의 특성이 변하기 때문에 정기적으로 오차 보정이 필요하다고 알려져 있다. 본 논문에서는 비동기 CDMA 시스템에서 안테나 배열 소자들 간의 진폭 이득과 위상 응답에 오차가 생길 때 온라인으로 보정 할 수 있는 알고리듬을 제안한다. 부공간(subspace) 기반의 알고리듬의 성능 평가와 분석 결과를 제시하기 위해 실험으로 측정한 데이터를 이용하였고, simulated annealing이라는 최적화 방법을 사용하여 부공간(subspace) 기반의 알고리듬에서 발생하는 초기값 문제를 해결하고 모의실험을 통해 확인하였다.