• Journal of Korean Society of Transportation
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• v.33 no.6
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• pp.520-530
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• 2015

This paper formulates the methodologies to estimate optimal congestion tolls from long-run and short-run perspectives and applies them to the highways of Seoul. An optimal long-run congestion toll is estimated with an optimal volume-capacity-ratio to minimize the total costs which consist of two components: road construction and maintenance costs and traveler costs. By contrast, an optimal short-run congestion toll is estimated with a supply-demand equilibrium which is determined by using a speed-flow function and a disaggregate modal choice model. The results of a long-run analysis for the Seobu urban expressway suggest the optimal volume-capacity-ratio of 1.35 and the optimal congestion toll of 503 Won per automobile kilometer. By contrast, those of a short-run analysis for the Mia-ro urban arterial suggest 1.31 and 420 Won, respectively. Although our results are to some degree dependent on the interest rate and time value assumed, one basic conclusion holds up: the congestions toll tested could generate substantial gains in social welfare if applied to Seoul.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.786-792
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• 2011

The present paper presents an optimal capacitor placement (OCP) algorithm for voltagestability enhancement. The OCP issue is represented using a mixed-integer problem and a highly nonlinear problem. The hybrid particle swarm optimization (HPSO) algorithm is proposed to solve the OCP problem. The HPSO algorithm combines the optimal power flow (OPF) with the primal-dual interior-point method (PDIPM) and ordinary PSO. It takes advantage of the global search ability of PSO and the very fast simulation running time of the OPF algorithm with PDIPM. In addition, OPF gives intelligence to PSO through the information provided by the dual variable of the OPF. Numerical results illustrate that the HPSO algorithm can improve the accuracy and reduce the simulation running time. Test results evaluated with the three-bus, New England 39-bus, and Korea Electric Power Corporation systems show the applicability of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.513-515
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• 2000

This paper deals with a method for determining an optimal operation strategy of dispersed generating sources considering thermal merits. The optimal operation of these sources can be determined by the principle of equal incremental fuel cost. This paper presents an optimal operation strategy using the Kuhn-Tucker's optimal conditions and also an priority method to decide the optimal location of those sources in power systems. The validity of the proposed algorithms are demonstrated using a model system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1272-1277
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• 2014

This article describes a path planning algorithm for fixed-wing UAVs when a real terrain should be considered. Nowadays, many UAVs are required to perform mission flights near given terrain for surveillance, reconnaissance, and infiltration, as well as flight altitude of many UAVs are relatively lower than typical manned aerial vehicles. Therefore, real terrain should be considered in path planning algorithms of fixed-wing UAVs. In this research, we have extended a spline-$RRT^*$ algorithm to three-dimensional planner. The spline-$RRT^*$ algorithm is a $RRT^*$ based algorithm, and it takes spline method to extend the tree structure over the workspace to generate smooth paths without any post-processing. Direction continuity of the resulting path is guaranteed via this spline technique, and it is essential factor for the paths of fixed-wing UAVs. The proposed algorithm confirm collision check during the tree structure extension, so that generated path is both geometrically and dynamically feasible in addition to direction continuity. To decrease degrees of freedom of a random configuration, we designed a function assigning directions to nodes of the graph. As a result, it increases the execution speed of the algorithm efficiently. In order to investigate the performance of the proposed planning algorithm, several simulations are performed under real terrain environment. Simulation results show that this proposed algorithm can be utilized effectively to path planning applications considering real terrain.

• Journal of the Society of Naval Architects of Korea
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• v.32 no.1
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• pp.9-16
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• 1995

The erection process planning is to decide erection strategy and sequence that satisfies dock duration. The erection scheduling is to decide erection date of each block. The load profile varies according to scheduling and it is related to building cost. It must be possible to simulate the various combinations of process plan and schedule for optimal planning. To develop the process planning system for optimal planning, the system that generate the sequence of erection automatically and the load leveling system are required. This paper suggests the method that generates the erection sequence. The load leveling should be done to all the ships in the same dock batch to get reliable results. In this case since the search space is very large, efficient optimization method is needed Our research achieved the load leveling system using Genetic Algorithm. This system made it possible to simulate various process plans to which schedule is considered.

• Journal of the Korea Society for Simulation
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• v.27 no.1
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• pp.1-13
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• 2018

Earthwork planning is one of the critical issues in a construction process management. For the construction process management, there are some different approaches such as optimizing construction with either mathematical methodologies or heuristics with simulations. This paper propose a simulated earthwork scenario and an optimal path for the simulation using a reinforcement learning. For reinforcement learning, we use two different Markov decision process, or MDP, formulations with interacting excavator agent and truck agent, sequenced learning, and independent learning. The simulation result shows that two different formulations can reach the optimal planning for a simulated earthwork scenario. This planning could be a basis for an automatic construction management.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.1
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• pp.76-83
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• 2010

There have been many studies regarding development of autonomous excavation system which is helpful in construction sites where repetitive jobs are necessary. Unfortunately, bucket trajectory planning was excluded from the previous studies. Since, the best use of excavator is to dig efficiently; purpose of this research was set to determine an optimized bucket trajectory in order to get best digging performance. Among infinite ways of digging any given path, criterion for either optimal or efficient bucket moves is required to be established. One method is to adopt work know-how from experienced excavator operator; However the work pattern varies from every worker to worker and it is hard to be analyzed. Thus, other than the work pattern taken from experienced operator, we developed an efficiency model to solve this problem. This paper presents a method to derive a bucket trajectory from optimization theory with empirical CLUB soil model. Path is greatly influenced by physical constraints such as geometry, excavator dimension and excavator workspace. By minimizing a energy function under these constraints, an optimal bucket trajectory could be obtained.

• Journal of Biosystems Engineering
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• v.24 no.4
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• pp.301-308
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• 1999

Path planning for field operation of agricultural machinery is an indispensible part for precision farming or autonomous field operation. In this study, two algorithms (I, II) of generating a time-based shortest operation path were suggested to plan an optimal operation of an agricultural tractor-implement in a rectangular shaped field. The algorithms were based on modification of a minimum spanning tree algorithm, and applied for tractor-implement operations. the generated path was consisted of round operation and returning operation sections. The number of round operation was determined from the condition that a tractor can turn smoothly at headlands. The performance of the algorithms was evaluated by the calculation number for path generation and the total path length generated. Their stability was affected by the number of returning operation, but the algorithm II was considered to be more stable. In addition, the performances of the developed algorithms were compared with those of the conventional field operations at selected field sizes and shapes. The results showed that the algorithms could reduce field operation time greatly. For a 100m$\times$40m field, the reduced path length was 78m. The study also included an user interface program for implementing the algorithms and generating GPS coordinates that could be used in GIS softwares for precision farming.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.37-52
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• 1998

In many distribution systems important cost reductions and/or service improvements may be achieved by adopting an efficient inventory policy and proper selection of facilities. These efficiency improvements and service enhancements clearly require an integrated approach towards various logistical planning functions. The areas of inventory control and transportation planning need to be closely coordinated. The purpose of this paper is to construct an integrated model that can minimize the total cost of the transportation and inventory systems between multiple origin and destination points, where in origin point i has the supply of commodities and in destination point j requires the commodities. In this case, demands of the destination points are assumed random variables which have a known probability distribution. Using the lot-size reorder-point policy and the safety stock level that minimize total cost we find optimal distribution centers which transport the commodities to the destination points and suggest an optimal inventory policy to the selected distribution center. We also show if a demand greater than one unit will occur at a particular time, we describe the approximate optional replenishment policy from computational results of this lot-size reorder-point policy. This model is formulated as a 0-1 nonlinear integer programming problem. To solve the problem, this paper proposes heuristic computational procedures and a computer program with UNIX C language. In the usefulness review, we show the meaning and validity of the proposed model and exhibit the results of a comparison between our approach and the traditional approach, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.471-476
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• 2015

This paper presents a maximum velocity trajectory planning algorithm for differential mobile robots with wheel velocity constraint to cope with physical limits in the joint space for two-wheeled mobile robots (TMR). In previous research, the convolution operator was able to generate a central velocity that deals with the physical constraints of a mobile robot while considering the heading angles along a smooth curve in terms of time-dependent parameter. However, the velocity could not track the predefined path. An algorithm is proposed to compensate an error that occurs between the actual and driven distance by the velocity of the center of a TMR within a sampling time. The velocity commands in Cartesian space are also converted to actuator commands to drive two wheels. In the case that the actuator commands exceed the maximum velocity the trajectory is redeveloped with the compensated center velocity. The new center velocity is obtained according to the curvature of the path to provide a maximum allowable velocity meaning a time-optimal trajectory. The effectiveness of the algorithm is shown through numerical examples.