• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.177-185
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• 2016

In this paper, an optimal planning system for operating transporters in shipyard is developed. The system is designed to utilize the geometries of shipyard, and manage the data of blocks and transporters directly. There are four major menus such as shipyard map management based on GIS, block transportation request, transporter management, and optimal transportation planning in the system. The geometries and properties of the shops, roads, and addresses are manipulated in the shipyard map management menu. The block transportation requests and the properties of transporters are managed in the block transportation request and transporter management menus, respectively. The optimum transportation is planned automatically for minimizing the unload times of the transporters, and the optimum transportation plans are confirmed and printed to the transporter drivers. The effectiveness of the system was verified through the application to a large-sized shipyard.

• ETRI Journal
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• v.15 no.3
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• pp.47-59
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• 1994

A capacity expansion planning problem with buy-or-lease decisions is considered. Demands for capacity are deterministic and are given period-dependently at each period. Capacity additions occur by buying or leasing a capacity, and leased capacity at any period is reconverted to original source after a fixed length of periods, say, lease period. All cost functions (buying, leasing and idle costs) are assumed to be concave. And shortages of capacity and disposals are not considered. The properties of an optimal solution are characterized. This is then used in a tree search algorithm for the optimal solution and other two algorithms for a near-optimal solution are added. And these algorithms are illustrated with numerical examples.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.1
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• pp.69-73
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• 1978

This paper deals with the problem of determining the optimal inventory-transportation policy of the idealistically simple inventory-transportation system with the following assumptions: (1) The system consists of a single central warehouse and a single local warehouse, (2) The planning horizon is finite, (3) Demand rate is fixed costant, and so forth. Developed is the algorithm by which to identify the optimal inventory policy which minimizes the total cost incurred to the system over the given finite planning horizon. A sample numerical example is presented along with a discussion of the possible applications of the approach used n the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1193-1196
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• 1996

Genetic algorithm(GA) is useful to find optimal solution without any special mathematical modeling. This study presents to search optimal path of Autonomous Mobile Robot(AMR) by using GA without encoding and decoding procedure. Therefore, this paper shows that the proposed algorithm using GA can reduce the computation time to search the optimal path.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.346-354
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• 1992

In the power-system, the active and reactive power levels of load bus randomly vary over days, months, and years which are stochastic in nature. This paper presents an algorithm for optimal Var planning considering the uncertainties of loads. The optimization problem is solved by a stochastic linear programming technique which can handle stochastic constraints to evaluate optimal Var requirement at load bus to maintain the voltage profile which results in probabilistic density function by stochastic Load Flow analysis within admissible range. The effectiveness of the proposed algorithm has been verified by the test on the IEEE-30 bus system.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.89.6-89
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• 2001

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 vehicle´s demand. This paper proposes a sub-optimal route planning mechanism of vehicles in urban areas using the non-network type immune system. Simulation is carried out using a cellular automaton model. This system announces a sub-optimal route to drivers in real time using VICS.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1258-1261
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• 1993

This paper presents a methodology of path planning and navigation for an autonomous mobile robot. A fast algorithm using decomposition technique, which computes the optimal paths between all pairs of nodes, is proposed for real-time calculation. The robot is controlled by fuzzy approximation reasoning. Our new methodology has been implemented on a mobile robot. The results show that the robot successfully navigates to its destination following the optimal path.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.790-793
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• 2008

Recently, Intelligent Excavating System(IES) for earthwork automation is on progress since the end of 2006 as a part of construction technology innovation projects in Ministry of Land, Transport and Maritime Affairs. Task Planning System(TPS), one of the detail core technologies of IES, is an optimal work planning system in conditions of effectiveness, safety and economic efficiency by analyzing the work environment data based on earthwork design and work environment recognition technology. For effective earthwork planning, the location of platform must be the most optimal spot for minimization of time, maximization of productivity and reduction of overlapped work spaces and unnecessariness. Besides, the decision of optimal platform location is to be based on the specifications and then is able to be converted with the local area calculation algorithm. This study explains the decision of optimal platform location on the basis of local area from the work space separate process and judges the effectiveness.

• International Journal of Naval Architecture and Ocean Engineering
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• v.10 no.4
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• pp.450-457
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• 2018

The determination of assembly sequence in general mechanical assemblies plays an important role in terms of manufacturing cost, duration and quality. In the production of ships and offshore plants, the consideration of productivity factors and welding deformation is crucial in determining the optimal assembly sequence. In shipbuilding and offshore industries, most assembly sequence planning has been done according to engineers' decisions based on extensive experience. This may result in error-prone planning and sub-optimal sequence, especially when dealing with unfamiliar block assemblies composed of dozens of parts. This paper presents an assembly sequence planning method for block assemblies. The proposed method basically considers geometric characteristics of blocks to determine feasible assembly sequences, as well as assembly process and productivity factors. Then the assembly sequence with minimal welding deformation is selected based on simplified welding distortion analysis. The method is validated using an asymmetric assembly model and the results indicate that it is capable of generating an optimal assembly sequence.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.7-13
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• 2008

This paper suggests a Path-planning algorithm for mobile agents. While there are a lot of studies on the path-planning for mobile agents, mathematical modeling of complex environment which constrained by spatio-temporally is very difficult and it is impossible to obtain the optimal solutions. In this paper, an optimal path-planning algorithm based on the graphic technique is presented. The working environment is divided into two areas, the one is free movable area and the other is not permissible area in which there exist obstacles and spatio-temporally constrained, and an optimal solution is obtained by using a new algorithm which is based on the well known ACO algorithm.