• Proceedings of the SAREK Conference
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• 2005.06a
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• pp.194-194
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• 2005

• Applied Biological Chemistry
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• v.6
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• pp.89-106
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• 1965

• Proceedings of the Korean Society of Crop Science Conference
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• 1998.04a
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• pp.29-30
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• 1998

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.286-286
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• 2004

• Proceedings of the PSK Conference
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• 2000.10a
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• pp.265.2-265.2
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• 2000

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.197.2-197.2
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• 2010

The study on the operation characteristics of solar space and water heating system with ground source heat pump (GSHP) as a back-up device was carried out. This system, called solar thermal and geothermal hybrid system (ST/G), was installed at Zero Energy Solar House II (KIER ZeSH-II) in Korea Institute of Energy Research. This ST/G hybrid system was developed to supply all thermal load in a house by renewable energy. The purpose of this study is to find out that this system is optimized and operated normally for the heating load of ZeSH-II. Experiment was continued for seven months, from October to April. The analysis was conducted as followings ; - the contribution of solar thermal system. - the appropriateness of GSHP as a back-up device. - the performance of solar thermal and ground source heat pump system respectively. - the adaptation of thermal peak load - the operation characteristics of hybrid system under different weather conditions. Finally the complementary measures for the system simplification was referred for the commercialization of this hybrid system.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.115-122
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• 2011

This research considers a system containing a manufacturing firm who generates waste material during manufacturing process, and a disposal firm who collects and disposes the waste material. Identification of the optimal number of pick ups and the amount of waste to be disposed at certain period of time in terms of cost minimization is studied. Two types of waste accumulation rates, constant and linearly increasing, are discussed and mathematical models are developed. It can be shown that the results for these two different types of waste accumulation differ in a wide range because of the difference in the way of how waste is accumulated, which disturbs the storage cost. An integrated model is also developed and discussed in which both the manufacturing firm and the disposal firm benefit from the coordination between the two parties. It is shown that the optimal policy adopted by the integrated approach can provide a strong and consistent cost-minimizing effect for both the manufacturing firm and the disposal firm over the existing approach. Finally, all the models are verified by a numerical example and the results are compared.

• Bulletin of the Korean Mathematical Society
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• v.52 no.1
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• pp.105-123
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• 2015

Let $f_{\beta}=h_{\beta}+\bar{g}_{\beta}$ and $F_a=H_a+\bar{G}_a$ be harmonic mappings obtained by shearing of analytic mappings $h_{\beta}+g_{\beta}=1/(2isin{\beta})log\((1+ze^{i{\beta}})/(1+ze^{-i{\beta}})\)$, 0 < ${\beta}$ < ${\pi}$ and $H_a+G_a=z/(1-z)$, respectively. Kumar et al. [7] conjectured that if ${\omega}(z)=e^{i{\theta}}z^n({\theta}{\in}\mathbb{R},n{\in}\mathbb{N})$ and ${\omega}_a(z)=(a-z)/(1-az)$, $a{\in}(-1,1)$ are dilatations of $f_{\beta}$ and $F_a$, respectively, then $F_a\tilde{\ast}f_{\beta}{\in}S^0_H$ and is convex in the direction of the real axis, provided $a{\in}[(n-2)/(n+2),1)$. They claimed to have verified the result for n = 1, 2, 3 and 4 only. In the present paper, we settle the above conjecture, in the affirmative, for ${\beta}={\pi}/2$ and for all $n{\in}\mathbb{N}$.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.171-180
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• 2009

Population learning algorithm (PLA) is a population-based method that was inspired by the similarities to the phenomenon of social education process in which a diminishing number of individuals enter an increasing number of learning stages. The study aims to develop a framework that repeatedly applying the PLA to solve the discrete resource constrained project scheduling problem with two objectives: minimizing project makespan and renewable resource availability, which are two most common concerns of management when a project is being executed. The PLA looping framework will provide a number of near Pareto optimal schedules for the management to make a choice. Different improvement schemes and learning procedures are applied at different stages of the process. The process gradually becomes more and more sophisticated and time consuming as there are less and less individuals to be taught. An experiment with ProGen generated instances was conducted, and the results demonstrated that the looping framework using PLA outperforms those using genetic local search, particle swarm optimization with local search, scatter search, as well as biased sampling multi-pass algorithm, in terms of several performance measures of proximity. However, the diversity using spread metric does not reveal any significant difference between these five looping algorithms.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.136-145
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• 2007

The selection of suppliers and the determination of order quantities to be placed with those suppliers are important decisions in a supply chain. In this research, a non-linear mixed integer programming model is presented to select suppliers and determine the order quantities. The model considers the purchasing cost which takes into account quantity discount, the cost of transportation, the fixed cost for establishing suppliers, the cost for holding inventory, and the cost of receiving poor quality parts. The capacity constraints for suppliers, quality and lead-time requirements for the parts are also taken into account in the model. Since the purchasing cost, which is a decreasing step function of order quantities, introduces discontinuities to the non-linear objective function, it is not easy to employ traditional optimization methods. Thus, a heuristic algorithm, called particle swarm optimization (PSO), is used to find the (near) optimal solution. However, PSO usually generates initial solutions randomly. To improve the PSO solution quality, a heuristic procedure is proposed to find an initial solution based on the average unit cost including transportation, purchasing, inventory, and poor quality part cost. The results show that PSO with the proposed initial solution heuristic provides better solutions than those with PSO algorithm only.