• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.624-627
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• 1992

Mathematical modeling is majorly divided into three parts: the derivation of models, the fitting of models to data, and the simulation of data from models. This paper focuses on the parameter optimization which is necessary for the fitting of models to data. The method of simulated annealing(SA) 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 SA phase. In this study, therfore, we propose a technique of determination of the starting temperature and cooling schedule for SA phase.

• 경영과학
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• 제18권2호
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• pp.117-124
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• 2001

This paper presents a machining parameter selection approach using an evolutionary computation (EC). In order to perform a successful material cutting process, the engineer is to select suitable machining parameters. Until now, it has been mostly done by the handbook look-up or solving optimization equations which is inconvenient when not in handy. The main thrust of the paper is to provide a handy machining parameter selection approach. The EC is applied to rapidly find optimal machining parameters for the user\\`s specific machining conditions. The EC is basically a combination of genetic a1gorithm and microcanonical stochastic simulated annealing method. The approach is described in detail with an application example. The paper concludes with a discussion on the potential of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.396-396
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• 2000

Multiperiod optimization is the key step to tackle the supply chain optimization problems. Taking supply and demand uncertainty or prediction into consideration during the process synthesis phase leads to the maximization of the profit for the long range time horizon. In this study, new algorithm based on the Genetic Algorithms is proposed for multiperiod optimization formulated in MINLP, GDP and hybrid MINLP/GDP. In this study, the focus is given especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is tried. and many heuristics are adopted for this purpose.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 봄 학술발표회 논문집
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• pp.245-253
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• 1998

Recently, the importance of multi-objective optimization techniques and stochastic search methods is increasing. The stochastic search methods have the concepts of the survival of the fittest and natural selection such as genetic algorithms(GA), simulated annealing(SA) and evolution strategies (ES). As many accidents of oil tankers cause marine pollution, oil tankers of double hull or mid deck structure are being built to minimize the marine pollution. For the improvement of oil tanker design technique, an efficient optimization technique is proposed in this study. Multi-objective optimization problem of weight and cost of double hull and mid deck tanker is formulated. Discrete design variables are used considering real manufacturing, and the concept of relative production cost is also introduced. The ES method is used as an optimization technique, and the ES algorithm was developed to generate a more efficient Pareto optimal set.

• ETRI Journal
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• 제41권3호
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• pp.326-336
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• 2019

A wireless power transfer technique can solve the power capacity problem in wireless rechargeable sensor networks (WRSNs). The charging strategy is a wide-spread research problem. In this paper, we propose a demand-based charging strategy (DBCS) for WRSNs. We improved the charging programming in four ways: clustering method, selecting to-be-charged nodes, charging path, and charging schedule. First, we proposed a multipoint improved K-means (MIKmeans) clustering algorithm to balance the energy consumption, which can group nodes based on location, residual energy, and historical contribution. Second, the dynamic selection algorithm for charging nodes (DSACN) was proposed to select on-demand charging nodes. Third, we designed simulated annealing based on performance and efficiency (SABPE) to optimize the charging path for a mobile charging vehicle (MCV) and reduce the charging time. Last, we proposed the DBCS to enhance the efficiency of the MCV. Simulations reveal that the strategy can achieve better performance in terms of reducing the charging path, thus increasing communication effectiveness and residual energy utility.

• 한국수소및신에너지학회논문집
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• 제30권5호
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• pp.455-464
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• 2019

Experiments were conducted to investigate the sensitivity of steel plate oxidation with temperature in a simulated furnace. Used steel plates were a general steel and a high tensile steel. Porous media burner (PM burner) used in model furnace was made for uniform temperature profile. The surrounding temperature was controlled by adjusting the flow rate of the mixture in the combustor. Oxide layer analysis was performed using SEM image analysis and EDS line scanning. Both steel sheets showed a tendency to increase the thickness of the steel sheet surface oxide layer as the temperature increases, and it was confirmed that the flaking phenomenon in surface oxidation layer appeared when the temperature was above a certain temperature.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2005년도 춘계 학술발표회 논문집
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• pp.273-280
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• 2005

The design of structural engineering optimization is to minimize the cost. This problem has many objective functions formulating section and shape as a function of the included discrete variables. simulated annealing, genetic algerian and TABU algerian are searching methods for optimum values. The object of this reserch Is comparing the result of TABU algorithm, and verifying the efficiency of TABU algorithm in structural optimization design field. For the purpose, this study used a solid truss of 25 elements having 10 nodes, and size optimization for each constraint and load condition of Geodesic ome, and shape optimization of Cable Dome for verifying spatial structures by the application of TABU algorithm.

• 한국진공학회지
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• 제10권3호
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• pp.283-288
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• 2001

본 연구에서는 분자동력학 방법을 사용하여 알루미늄 덩어리 충돌에 관하여 연구하였다. 충돌에 따른 운동량 및 충격력 변화를 통하여, 덩어리 충돌은 단일입자충돌(single particle collision) 특성 일부와 선형사슬충돌(linear chain collisions) 특성 일부를 가지는 것을 살펴보았다. 또한 연속적인 덩어리 증착을 통하여 성장된 박막의 특성을 살펴보았다 원자당 에너지가 너무 낮은 경우보다는 일정 에너지 이상에서 혼합(intermixing) 발생이 잘 이루어지며 짝은 어닐링 공정으로 좋은 박막을 얻을 수 있다는 것을 살펴보았다.

• Industrial Engineering and Management Systems
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• 제10권1호
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• pp.7-14
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• 2011

In solving the Job Shop Scheduling Problem, the best solution rarely is completely random; it follows one or more rules (heuristics). The Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing, and Tabu search, which belong to the Evolutionary Computations Algorithms (ECs), are not efficient enough in solving this problem as they neglect all conventional heuristics and hence they need to be hybridized with different heuristics. In this paper a new algorithm titled "Shaking Optimization Algorithm" is proposed that follows the common methodology of the Evolutionary Computations while utilizing different heuristics during the evolution process of the solution. The results show that the proposed algorithm outperforms the GA, PSO, SA, and TS algorithms, while being a good competitor to some other hybridized techniques in solving a selected number of benchmark Job Shop Scheduling problems.

• International Journal of Aeronautical and Space Sciences
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• 제15권1호
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• pp.63-73
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• 2014

For robust stability analysis of parameters uncertainty missiles, the traditional frequency domain method can only analyze each respective channel at several interval points within uncertain parameter space. Discontinuous calculation and couplings between channels will lead to inaccurate analysis results. A method based on the ${\nu}$-gap metric is proposed, which is able to comprehensively evaluate the robust stability of missiles with uncertain parameters; and then a genetic-simulated annealing hybrid optimization algorithm, which has global and local searching ability, is used to search for a parameters combination that leads to the worst stability within the space of uncertain parameters. Finally, the proposed method is used to analyze the robust stability of a re-entry missile with uncertain parameters; the results verify the feasibility and accuracy of the method.