• Journal of Power System Engineering
• /
• v.8 no.2
• /
• pp.45-52
• /
• 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.

• International Journal of CAD/CAM
• /
• v.12 no.1
• /
• pp.9-19
• /
• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1993.04a
• /
• pp.341-341
• /
• 1993

• Proceedings of the KSME Conference
• /
• 2000.11a
• /
• pp.381-386
• /
• 2000

Simple spring-damper-mass models have been widely used to understand whole-body vertical biodynamic response characteristics of the seated vehicle driver. However, most previous models have not considered about the non-rigid masses(wobbling masses). A simple mechanical model of seated human body developed in this study included the torso represented by a rigid and a wobbling mass. Within the 0.5-20Hz frequency range and for excitation amplitudes maintained below $5ms^{-2}$, this 4-degree-of-freedom driver model is proposed to satisfy the measured vertical vibration response characteristics defined from a synthesis of published data for subjects seated erect without backrest support. The parameters are identified by using the combinatorial optimization technique, simulated annealing method. The model response was found to be provided a closer agreement with the response characteristics than previously published models.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.256-256
• /
• 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 Korean Operations Research and Management Science Society
• /
• v.18 no.2
• /
• pp.83-103
• /
• 1993

This paper addresses an optimization problem faced by a multi-server and multi-class customer system in manufacturing facilities and service industries. This paper presents a model of an integrated problem of server allocation and customer type partitioning. We approximate the problem through two types of models to make it tractable. As soution approach, the simulated annealing heuristic is constructed based on the general simulated annealing method. Computational results are presented.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.44 no.5
• /
• pp.42-49
• /
• 2007

This paper introduces a study on reliability-driven device placement using simulated annealing algorithm which can be applicable to MCM or electronic systems embedded in a spacecraft running at thermal conduction environment. Reliability of the unit's has been predicted with the devices' junction temperatures calculated from FDM solver and optimized by simulated annealing algorithm. Simulated annealing in this paper adopts swapping devices method as a perturbation. This paper describes and compares the optimization simulation results with respect to two objective functions: minimization of failure rate and minimization of average junction temperature. Annealing temperature variation simulation case and equilibrium coefficient variation simulation case are also presented at the two respective objective functions. This paper proposes a new approach for reliability optimization of MCM and electronic systems considering those simulation results.

• ETRI Journal
• /
• v.15 no.3
• /
• pp.1-26
• /
• 1994

Simulated annealing is an attractive, but expensive, heuristic method for approximating the solution to combinatorial optimization problems. Attempts to parallel simulated annealing, particularly on distributed memory multicomputers, are hampered by the algorithm's requirement of a globally consistent system state. In a multicomputer, maintaining the global state S involves explicit message traffic and is a critical performance bottleneck. To mitigate this bottleneck, it becomes necessary to amortize the overhead of these state updates over as many parallel state changes as possible. By using this technique, errors in the actual cost C(S) of a particular state S will be introduced into the annealing process. This paper places analytically derived bounds on this error in order to assure convergence to the correct optimal result. The resulting parallel simulated annealing algorithm dynamically changes the frequency of global updates as a function of the annealing control parameter, i.e. temperature. Implementation results on an Intel iPSC/2 are reported.

• Proceedings of the KIEE Conference
• /
• 1992.07a
• /
• pp.288-289
• /
• 1992

The method of simulated annealing is a technique that has recently attracted significant attention as suitable for optimization problem of very large scale. If the temperature is too high, then some of the structure created by the heuristic will be destroyed and unnecessary extra work will be done. If it is too low then solution is lost, similar to the case of a quenching cooling schedule in the Simulated Annealing (SA) phase. Therefore, a crucial issue in this study is the determination of the starting temperature and cooling schedule for SA phase.

• International Journal of Reliability and Applications
• /
• v.13 no.2
• /
• pp.91-104
• /
• 2012

Sarhan and Kundu (2009) introduced a new distribution named as the generalized linear failure rate distribution. This distribution generalizes several well known distributions. The probability density function of the generalized linear failure rate distribution can be right skewed or unimodal and its hazard function can be increasing, decreasing or bathtub shaped. This distribution can be used quite effectively to analyze lifetime data in place of linear failure rate, generalized exponential and generalized Rayleigh distributions. In this paper, we apply the simulated annealing algorithm to obtain the maximum likelihood point estimates of the parameters of the generalized linear failure rate distribution. Simulated annealing algorithm can not only find the global optimum; it is also less likely to fail because it is a very robust algorithm. The estimators obtained using simulated annealing algorithm have been compared with the corresponding traditional maximum likelihood estimators for their risks.