• Journal of the military operations research society of Korea
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• v.7 no.2
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• pp.63-99
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• 1981

The generalized goal decomposition model proposed by Ruefli as a single period decision model is presented for the purpose of a review and extended to make a multiple period planning model. The multiple period planning model in the three level organization is formulated with, linear goal deviations by introducing the goal programming method. Dynamic formulation using the generalized goal decomposition model for each single period problem is also presented. An iterative search algorithm is presented as an appropriate solution method of the dynamic formulation of the multiple period planning model.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1921-1926
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• 2003

We build a local minimum free motion planning for mobile robots considering dynamic environments by simple sensor fusion assuming that there are unknown obstacles which can be detected only partially at a time by proximity sensors and can be cleaned up or moved slowly (dynamic environments). Potential field is used as a basic platform for the motion planning. To clear local minimum problem, the partial information on the obstacles should be memorized and integrated effectively. Sets of linked line segments (SLLS) are proposed as the integration method. Then robot's target point is replaced by virtual target considering the integrated sensing information. As for the main proximity sensors, we use laser slit emission and simple web camera since the system gives more continuous data information. Also, we use ultrasonic sensors as the auxiliary sensors for simple sensor fusion considering the advantages in that they give exact information about the presence of any obstacle within certain range. By using this sensor fusion, the dynamic environments can be dealt easily. The performance of our algorithm is validated via simulations and experiments.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.10
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• pp.582-590
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• 2000

A fast optimal path planning algorithm using the analog Cellular Nonlinear Circuits(CNC) is proposed. The analog circuits based optimal path planning is very useful since most of the optimal path planning problems require real time computation. There has already been a previous study to implement the dynamic programming with analog circuits. However, it could not be applied for the practically large size of problems since the algorithm employs the mechanism of reducing its input current/voltage by the amount of cost, which causes outputs of distant cells to become zero. In this study, a subgoal-based dynamic programming algorithm to compute the optimal path is proposed. In the algorithm, the optimal paths are computed regardless of the distance between the starting and the goal points. It finds subgoals starting from the starting point when the output of the starting cell is raised from its initial value. The subgoal is set as the next initial position to find the next subgoal until the final goal is reached. The global optimality of the proposed algorithm is discussed and two different kinds of simulations have been done for the proposed algorithm.

• Journal of Navigation and Port Research
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• v.31 no.2
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• pp.141-149
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• 2007

The competitiveness of container terminals hinges on minimizing the time vessels spend in port and on schedule services. Many previous researches on container terminals have tried to optimize the equipment allocation plan and to improve the activity of resources. Nevertheless, there have been few researches conducted on yard tractors, which move containers between the quay and the yard. The aim of this study is to propose the use of Real Time Location Systems (RTLS) based Dynamic Planning for yard tractors. Only RFID (Radio Frequency Identification) tags, which are attached to yard tractors, are able to support RTLS implementation. The system can provide real time job ordering in terms of load balancing using the information on location, in regards to the movement of yard tractors. This study will present the practical feasibility of RTLS, which can ultimately reduce the congestion of Hot Queues in container terminals. As a result, container terminals can be more productive and competitive. In order to accomplish the purpose of this study, we examined previous studies on the competitiveness of container terminals and summarized the potential of RTLS using RFID. In addition, we identified the role of yard tractors and proposed the two rules of Dynamic Planning for the yard tractors. We then fulfilled computational experiments on how yard tractors carrying containers by RTLS ordering Finally, the benefits and the implications of this study are discussed.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.1
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• pp.61-69
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• 2021

Recently, autonomous navigation technology is actively being developed due to the increasing demand of an unmanned surface vehicle(USV). Local planning is essential for the USV to safely reach its destination along paths. the dynamic window approach(DWA) algorithm is a well-known navigation scheme as a local path planning. However, the existing DWA algorithm does not consider path line tracking, and the fixed weight coefficient of the evaluation function, which is a core part, cannot provide flexible path planning for all situations. Therefore, in this paper, we propose a new DWA algorithm that can follow path lines in all situations. Fixed weight coefficients were trained using reinforcement learning(RL) which has been actively studied recently. We implemented the simulation and compared the existing DWA algorithm with the DWA algorithm proposed in this paper. As a result, we confirmed the effectiveness of the proposed algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.1
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• pp.39-46
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• 2012

An unmanned aerial vehicle (UAV) is a powered aerial vehicle that does not carry a human operator, uses aerodynamic forces to provide vehicle lift, can fly autonomously or be piloted remotely, can be expendable or recoverable, and can carry a lethal or non-lethal payload. An UAV is very important weapon system and is currently being employed in many military missions (surveillance, reconnaissance, communication relay, targeting, strike, etc.) in the war. To accomplish UAV's missions, guarantee of survivability should be preceded. The main objective of this study is a local path planning to maximize survivability for UAV on the battlefield of dynamic threats (obstacles, surface-to-air missiles, radar etc.). A local path planning is capable of producing a new path in response to environmental changes. This study suggests a $Smart$ $A^*$ (Smart A-star) algorithm for local path planning. The local path planned by $Smart$ $A^*$ algorithm is compared with the results of existing algorithms ($A^*$ $Replanner$, $D^*$) and evaluated performance of $Smart$ $A^*$ algorithm. The result of suggested algorithm gives the better solutions when compared with existing algorithms.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.71-79
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• 2010

This paper addresses capacity expansion planning model of distribution center under usability of public distribution center. For discrete and finite time periods, demands for distribution center increase dynamically. The capacity expansion planning is to determine the capacity expansion size of private distribution center and usage size of public distribution center for each period through the time periods. The capacity expansion of private distribution center or lease usage of public distribution center must be done to satisfy demand increase for distribution center. The costs are capacity expansion cost and excess capacity holding cost of private distribution center, lease usage cost of public distribution center. Capacity expansion planning of minimizing the total costs is mathematically modelled. The properties of optimal solution are characterized and a dynamic programming algorithm is developed. A numerical example is shown to explain the problem.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.127-134
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• 2010

In this paper, a hybrid semi-3D path planning algorithm combining Virtual Tangential Vector(VTV) and fuzzy control is proposed. 3D dynamic environmental factors are reflected to the 2D path planning model, VTV. As a result, the robot can control direction from 2D path planning algorithm VTV and speed as well depending on the fuzzy inputs such as the distance between the robot and obstacle, roughness and slope. Performances and feasibilities of the suggested method are demonstrated by using Matlab simulations. Simulation results show that fuzzy rules and obstacle avoidance methods are working properly toward virtual 3D environments. The proposed hybrid semi-3D path planning is expected to be well applicable to a real life environment, considering its simplicity and realistic nature of the dynamic factors included.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.686-693
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• 2013

Generation Expansion Planning (GEP) is one of the most important decision-making activities in electric utilities. Least-cost GEP is to determine the minimum-cost capacity addition plan (i.e., the type and number of candidate plants) that meets forecasted demand within a pre specified reliability criterion over a planning horizon. In this paper, Differential Evolution (DE), and Opposition-based Differential Evolution (ODE) algorithms have been applied to the GEP problem. The original GEP problem has been modified by incorporating Virtual Mapping Procedure (VMP). The GEP problem of a synthetic test systems for 6-year, 14-year and 24-year planning horizons having five types of candidate units have been considered. The results have been compared with Dynamic Programming (DP) method. The ODE performs well and converges faster than DE.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.396-401
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• 2004

Recently a framework for the cognition-based navigational planning of a mobile robot on dynamic environment has been proposed, and simulation results applied it to the static environment been presented [1]. In this paper, we propose a linguistic map-based framework for the navigational planning of mobile robots, which is applicable to the dynamic environment including not only static obstacles but also dynamic obstacles such as temporal-spatio obstacles, by extending Lee et al. 's framework, and provide computer simulation results obtained by applying to a mobile robot on the dynamic environment in order to show the validity of the proposed algorithm.