• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.62-63
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• 2016

Existing studies relative to enhancing sustainability of earth-work are mainly involved in the performance of construction equipments. They assume that there is no variation of the engine power and fuel consumption and classify the dozer operation into working and idle conditions. They enable to find the most eco-friendly equipment fleet deployment plan. However, they are confined in that they do not provide a measure to assess the sustainability of the operation plan and suggest optimal alternative(s). This paper presents a method that identifies an optimal dozer operation plan that assures sustainability by reducing fuel consumption of the equipment. The method computes the dozer operation productivity using engine-torque-output map provided by equipment manufacturers. Indeed, it identifies the eco-dozing operation that minimizes fuel consumption and maximizes the target productivity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1133-1151
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• 2010

Energy balanced consumption routing is based on assumption that the nodes consume energy both in transmitting and receiving. Lopsided energy consumption is an intrinsic problem in low-cost sensor networks characterized by multihop routing and in many traffic overhead pattern networks, and this irregular energy dissipation can significantly reduce network lifetime. In this paper, we study the problem of maximizing network lifetime through balancing energy consumption for uniformly deployed low-cost sensor networks. We formulate the energy consumption balancing problem as an optimal balancing data transmitting problem by combining the ideas of corona cluster based network division and optimized transmitting state routing strategy together with data transmission. We propose a localized cluster based routing scheme that guarantees balanced energy consumption among clusters within each corona. We develop a new energy cluster based routing protocol called "OECR". We design an offline centralized algorithm with time complexity O (log n) (n is the number of clusters) to solve the transmitting data distribution problem aimed at energy balancing consumption among nodes in different cluster. An approach for computing the optimal number of clusters to maximize the network lifetime is also presented. Based on the mathematical model, an optimized energy cluster routing (OECR) is designed and the solution for extending OEDR to low-cost sensor networks is also presented. Simulation results demonstrate that the proposed routing scheme significantly outperforms conventional energy routing schemes in terms of network lifetime.

• Current Photovoltaic Research
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• v.11 no.4
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• pp.134-143
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• 2023

Efforts are being made to respond to global warming. Interest in and demand for the private sector-led RE100 campaign is also increasing. Self-built solar power generation, one of the implementation tools for RE100, is not expanding. However, it can be an economical means of implementation in the long run. In this study, we intend to analyze the impact on the optimal ratio of self-solar power generation using HOMER simulation. OPR defines the optimal solar power generation ratio and looks into what changes there are in the optimal solar power ratio when self-power consumption increases and external power purchase price changes. As a result, the optimal rate of self-solar power generation has a low impact even if self-power consumption increases. As the external power unit price increases, the optimal ratio increases, and at a power unit price of 100 KRW/kWh, OPR is 24%; at 200 KRW/kWh OPR is 31%; and at 300 KRW/kWh OPR is 34%. This shows that the electricity price replaced during the life cycle has a high impact on the economic feasibility of solar power generation. However, when the external power unit price reached a certain level, the increase in OPR decreased. This shows that it is difficult for domestic companies to achieve RE100 based on the economic feasibility of solar energy alone. Therefore, efforts are needed to supply renewable energy in the public sector.

• Journal of Astronomy and Space Sciences
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• v.25 no.4
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• pp.361-374
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• 2008

Recently, satellite formation flying has been a topic of significant research interest in aerospace society because it provides potential benefits compared to a large spacecraft. Some techniques have been proposed to design optimal formation trajectories minimizing fuel consumption in the process of formation configuration or reconfiguration. In this study, a method is introduced to build fuel-optimal trajectories minimizing a cost function that combines the total fuel consumption of all satellites and assignment of fuel consumption rate for each satellite. This approach is based on collocation and nonlinear programming to solve constraints for collision avoidance and the final configuration. New constraints of nonlinear equality or inequality are derived for final configuration, and nonlinear inequality constraints are established for collision avoidance. The final configuration constraints are that three or more satellites should form a projected circular orbit and make an equilateral polygon in the horizontal plane. Example scenarios, including these constraints and the cost function, are simulated by the method to generate optimal trajectories for the formation configuration and reconfiguration of multiple satellites.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.14 no.1
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• pp.16-21
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• 2018

This work aims to develop a platform to investigate the effect of operation schedules on the building energy consumption and to derive a simulation model based optimal start and stop daily strategy. An open-source building energy simulation tool DOE2 is used for the engine, and the developed simulation model is validated using ASHRAE guideline 14. The effect of late-start/early-stop operation of HVAC system on the daily building energy consumption was analyzed using the developed simulation model. It was found that about 10% of energy consumption cut was possible using the control strategy for an hour of advance of the stop operation, and about 3% per an hour of delay of the start operation.

• Management Science and Financial Engineering
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• v.20 no.2
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• pp.13-25
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• 2014

We investigate an optimal retirement time and consumption/investment policy of a wage earner who expects to find a better investment opportunity after retirement by being freed from other work and participating fully in the financial market. We obtain a closed form solution to the optimization problem by using a dynamic programming method under general time-separable von Neumann-Morgenstern utility. It is optimal for the wage earner to retire from work if and only if his wealth exceeds a certain critical level which is obtained from a free boundary value problem. The wage earner consumes less and takes more risk than he would without anticipation of a better investment opportunity.

• Bulletin of the Korean Mathematical Society
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• v.60 no.4
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• pp.1101-1129
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• 2023

In this study we propose a model of optimal retirement, consumption and portfolio choice of an individual agent, which encompasses a large class of the models in the literature, and provide a methodology to solve the model. Different from the traditional approach, we consider the problems before and after retirement simultaneously and identify the difference in the dual value functions as the utility value of lifetime labor. The utility value has an option nature, namely, it is the maximized value of choosing the retirement time optimally and we discover it by solving a variational inequality. Then, we discover the dual value functions by using the utility value. We discover the value function and optimal policies by establishing a duality between the value function and the dual value function. The model and approach offer a significant advantage for computation of optimal policies for a large class of problems.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.741-750
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• 2021

The budget deficit is closely related to expansionary fiscal policy as a fiscal instrument to encourage economic growth. This study aims to apply optimal control theory in the Keynesian macroeconomic model for the economy, so that optimal growth can be found. Macroeconomic variables include GDP, consumption, investment, exports, imports, and budget deficit as control variables. This study uses secondary data in the form of time series, the time period 1990 to 2018. Performing optimal control will result in optimal fiscal policy. The optimal determination is done through simulation, for the period 2019-2023. The discrete optimal control problem is to minimize the objective function in the form of a quadratic function against the deviation of the state variable and control variable from the target value and the optimal value. Meanwhile, the constraint is Keynes' macroeconomic model. The results showed that the optimal value of macroeconomic variables has a deviation from the target values consisting of: consumption, investment, exports, imports, GDP, and budget deficit. The largest deviation from the average during the simulation occurs in GDP, followed by investment, exports, and the budget deficit. Meanwhile, the lowest average deviation is found in imports.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.5
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• pp.414-424
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• 2015

In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.

• Journal of the Korean Operations Research and Management Science Society
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• v.36 no.1
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• pp.1-11
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• 2011

This article examines the impact of electronic commerce on environmental welfare. In particular, we analyze a game model of price competition between offline and online firms when consumption taxes are imposed on both offline and online transactions that produce environmental pollution. We investigate the properties of optimal taxation between offline and online markets and demonstrate that there is an optimal difference between the two taxes, depending upon not only the transaction cost between offline and online consumption, but also the environmental damage cost. We also investigate the effect of tax-free online transactions on tax revenues, and the financial feasibility of the optimal taxation.