• 대한산업공학회지
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• 제25권4호
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• pp.466-475
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• 1999

A backward Dynamic Programming(DP) model for the optimal facility replacement decision problem during a finite planning horizon is presented. Multiple alternative challengers to a current defender are considered. All facilities are assumed to have finite service lives. The objective of the DP model is to maximize the profit over a finite planning horizon. As for the cost elements, purchasing cost, maintenance costs and repair costs as well as salvage value are considered. The time to failure is assumed to follow a weibull distribution and the maximum likelihood estimation of Weibull parameters is used to evaluate the expected cost of repair. To evaluate the revenue, the rate of operation during a specified period is employed. The cash flow component of each challenger can vary independently according to the time of occurrence and the item can be extended easily. The effects of inflation and the time value of money are considered. The algorithm is illustrated with a numerical example. A MATLAB implementation of the model is used to identify the optimal sequence and timing of the replacement.

• 한국정밀공학회지
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• 제15권9호
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• pp.101-110
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• 1998

In process planning for 3D pocket machining, the critical issues for the optimal process planning are the generation of cutting layers and the tool selection for each cutting layers as well as the other factors such as the determination of machining types, tool path, etc. This paper describes the optimal tool selection on a single cutting layer for 2D pocket machining, the generation of cutting layers for 3D pocket machining, the determination of the thickness of each cutting layers, the determination of the tool combinations for each cutting layers and also the development of an algorithm for determining the machining sequence which reduces the number of tool exchanges, which are based on the backward approach. The branch and bound method is applied to select the optimal tools for each cutting layer, and an algorithmic procedure is developed to determine the machining sequence consisting of the pairs of the cutting layers and cutting tools to be used in the same operation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.24.2-24
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• 2001

In this paper, the authors present a row dynamic route planning by Q-learning. The proposed algorithm is executed in a cellular automation based traffic simulator, which is also newly created. In Vehicle Information and Communication System(VICS), which is an active field of Intelligent Transport System(ITS), information of traffic congestion is sent to each vehicle at real time. However, a centralized navigation system is not realistic to guide millions of vehicles in a megalopolis. Autonomous distributed systems should be more flexible and scalable, and also have a chance to focus on each vehicles demand. In such systems, each vehicle can search an own optimal route. We employ Q-learning of the reinforcement learning method to search an optimal or sub-optimal route, in which route drivers can avoid traffic congestions. We find some applications of the reinforcement learning in the "static" environment, but there are ...

• 신재생에너지
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• 제19권3호
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• pp.1-12
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• 2023

This study aims to evaluate the optimal size of the hydrogen facility to be installed in a zero-energy district in terms of load matching and facility efficiency. A mismatch between energy generation and consumption is a common occurrence in zero-energy districts. This mismatch adversely effects the energy grid. However, using an energy carrier such as hydrogen can solve this problem. To determine the optimal size of hydrogen fuel cells to be used on-site, simulation of hydrogen installation is required at both district-and building- levels. Each case had four operating schedules. Therefore, we evaluated eight scenarios in terms of load matching, heat loss, and facility operational efficiency. The results indicate that district-level installation of hydrogen facilities enables more efficient energy use. Additionally, based on the proposed model, we can calculate the optimal size of the hydrogen facility.

• 한국해양공학회지
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• 제37권3호
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• pp.122-128
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• 2023

Autonomous berthing is a crucial technology for autonomous ships, requiring optimal trajectory planning to prevent collisions and minimize time and control efforts. This paper presents a two-phase, two-point boundary value problem (TPBVP) strategy for creating an optimal berthing trajectory for a twin-propeller, twin-rudder ship with autonomous berthing capabilities. The process is divided into two phases: the approach and the terminal. Tunnel thruster use is limited during the approach but fully employed during the terminal phase. This strategy permits concurrent optimization of the total trajectory duration, individual phase trajectories, and phase transition time. The efficacy of the proposed method is validated through two simulations. The first explores a scenario with phase transition, and the second generates a trajectory relying solely on the approach phase. The results affirm our algorithm's effectiveness in deciding transition necessity, identifying optimal transition timing, and optimizing the trajectory accordingly. The proposed two-phase TPBVP approach holds significant implications for advancements in autonomous ship navigation, enhancing safety and efficiency in berthing operations.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1983년도 하계학술회의강연.논문초록집
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• pp.156-158
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• 1983

• 기술혁신연구
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• 제5권1호
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• pp.266-287
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• 1997

The purpose of this paper is to purpose methods and procedures by which we can set up technology planning scheme essential for R'||'&'||'D(or technology) planning in public sector (governmental and government-sponsored institutions), and can develop and select "main R'||'&'||'D projects" which are crucial to R'||'&'||'D planning, were quite specifically discussed in case of I'||'&'||'T(Information '||'&'||' Telecommunications) sector, so that they may not remain theoretical but may be practically applicable to real R'||'&'||'D programs. In this paper, the concept of technology planning was defined as a procedure for establishing nominal planning to acquire technologies efficiently for a specific sector. More detailed definition optimal technology-acquisition strategy, i.e., analyzing technological development '||'&'||' environ-ment, establishing R'||'&'||'D objectives as promising technology opportunities, selecting main R'||'&'||'D projects, allocating resources and so on."The"main R'||'&'||'D projects by technology sectors and by planning phases and then deciding on priority. Scoring method was rsed in assessment phase. Summing up, this paper suggested technology planning scheme of methods and procedures for sorting out required technologies, developing and assessing public R'||'&'||'D projects, and finally selecting main R'||'&'||'D projects.

• International Journal of Control, Automation, and Systems
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• 제6권3호
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• pp.401-412
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• 2008

This paper discusses a design methodology of cooperative path planning for dynamical multi-agent systems with spatial and temporal constraints. The cooperative behavior of the multi-agent systems is specified in terms of the objective function in an optimization formulation. The path of achieving cooperative tasks is then generated by the optimization formulation constructed based on a differential flatness approach. Three scenarios of multi-agent tasking are proposed at the cooperative task planning framework. Given agent dynamics, both spatial and temporal constraints are considered in the path planning. The path planning algorithm first finds trajectory curves in a lower-dimensional space and then parameterizes the curves by a set of B-spline representations. The coefficients of the B-spline curves are further solved by a sequential quadratic programming solver to achieve the optimization objective and satisfy these constraints. Finally, several illustrative examples of cooperative path/task planning are presented.

• 로봇학회논문지
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• 제6권3호
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• pp.255-262
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• 2011

Many intelligent robots have to be given environmental information to perform tasks. In this paper an intelligent robot, that is, a cleaning robot used a sensor fusing method of two sensors: LRF and StarGazer, and then was able to obtain the information. Throughout wall following using laser displacement sensor, LRF, the working area is built during the robot turn one cycle around the area. After the process of wall following, a path planning which is able to execute the work effectively is established using flow network algorithm. This paper describes an algorithm for minimal turning complete coverage path planning for intelligent robots. This algorithm divides the whole working area by cellular decomposition, and then provides the path planning among the cells employing flow networks. It also provides specific path planning inside each cell guaranteeing the minimal turning of the robots. The proposed algorithm is applied to two different working areas, and verified that it is an optimal path planning method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.205-207
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• 1993

Distribution planning requires comprehensive knowledge about not only distribution but also transmission/subtransmission system expansion plan. At the same time, distribution planning is very time consuming and a series of routine job which involves a lot of experience and efforts of planning engineers. Since the quality of distribution planning depends upon the ability of planning engineers, the economy of investment should be taken into consideration. The object of this study is to establish a computerized distribution planning system which helps distribution engineers finding a new system expansion plan. It provides the engineers with at optimal system expansion plan which satisfies the condition of both reliability and economy.