• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4726-4731
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• 2011

This paper proposed the algorithm to select optimal grinding condition for plunge grinding in the batch production unit. In order to apply to the proposed algorithm, the state variable for plunge grinding process was defined and the optimal grinding condition for each cycle in batch production was decided by genetic algorithm. Based on the optimized grinding condition in each cycle, the optimal grinding condition for whole batch production was selected by dynamic programming. The proposed algorithm was evaluated by computer simulation.

• Journal of the Chungcheong Mathematical Society
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• v.25 no.2
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• pp.277-281
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• 2012

I study an optimal consumption and portfolio selection problem with regime-switching using a dynamic programming method. With constant relative risk aversion (CRRA) utility I obtain optimal solutions in closed-form.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.3
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• pp.98-105
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• 2012

Recently, most of the countries started to regulate the emission of vehicle because of the global warming. The engine scooter is also one of the factor which cause the pollution. The hybrid system of a vehicle has many advantages such as fuel saving and emission reduction. The purpose of this study is to choose optimal size of engine, motor and battery for hybrid scooter system using Dynamic programming. The dynamic programming is an effective method to find an optimal solution for the complicated nonlinear system, which contains various constraints of control variables. The power source size of hybrid scooter was chosen through the backward simulator using dynamic programming. From the analysis, we choose the optimal size of each power source. To verify the optimal size of the power source, the Forward simulation was carried out. As a result, the fuel efficiency of hybrid scooter has significantly increased in comparison with that of engine scooter.

• Journal of Ocean Engineering and Technology
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• v.29 no.3
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• pp.263-269
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• 2015

This paper proposes a new approach for solving the weather routing problem by dividing it into two phases with the goal of fuel saving. The problem is to decide two optimal variables: the heading angle and speed of the ship under several constraints. In the first phase, the optimal route is obtained using the Real-Time Adaptive A* algorithm with a fixed ship speed. In other words, only the heading angle is decided. The second phase is the speed scheduling phase. In this phase, the original problem, which is a nonlinear optimization problem, is converted into a geometric programming problem. By solving this geometric programming problem, which is a convex optimization problem, we can obtain an optimal speed scheduling solution very efficiently. A simple case of numerical simulation is conducted in order to validate the proposed method, and the results show that the proposed method can save fuel compared to a constant engine output voyage and constant speed voyage.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.329-337
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• 2016

With the increasing deployment of distributed generators in the distribution system, a very large search space is required when dynamic programming (DP) is applied for the optimized dispatch schedules of voltage and reactive power controllers such as on-load tap changers, distributed generators, and shunt capacitors. This study proposes a new optimal voltage and reactive power scheduling method based on dynamic programming with a heuristic searching space reduction approach to reduce the computational burden. This algorithm is designed to determine optimum dispatch schedules based on power system day-ahead scheduling, with new control objectives that consider the reduction of active power losses and maintain the receiving power factor. In this work, to reduce the computational burden, an advanced voltage sensitivity index (AVSI) is adopted to reduce the number of load-flow calculations by estimating bus voltages. Moreover, the accumulated switching operation number up to the current stage is applied prior to the load-flow calculation module. The computational burden can be greatly reduced by using dynamic programming. Case studies were conducted using the IEEE 30-bus test systems and the simulation results indicate that the proposed method is more effective in terms of saving electric charges and improving the voltage profile than loss minimization.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.29 no.12
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• pp.638-644
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• 2017

Optimal cooling operation algorithm was developed based on a simulation case of a single family house model equipped with renewable energy facility. EnergyPlus simulation results were used as virtual test data. The model contained three energy storage elements: thermal heat capacity of the living room, chilled water storage tank, and battery. Their charging and discharging schedules were optimized so that daily electricity bill became minimal. As an optimization tool, linear programming was considered because it was possible to obtain results in real time. For its adoption, EnergyPlus-based house model had to be linearly approximated. Results of this study revealed that dynamic cooling load of the living room could be approximated by a linear RC model. Scheduling based on the linear programming was then compared to that by a nonlinear optimization algorithm which was made using GenOpt developed by a national lab in USA. They showed quite similar performances. Therefore, linear programming can be a practical solution to optimal operation scheduling if linear dynamic models are tuned to simulate their real equivalents with reasonable accuracy.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.226-227
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• 2007

Significant increase of container flows in marine terminals requires more efficient automatic port systems. This paper presents a novel routing and collision avoidance algorithm of linear motor based shuttle cars using random access sequence dynamic programming (RAS DP). The proposed RAS DP is accomplished online for determining optimal paths for each shuttle car.

• Management Science and Financial Engineering
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• v.13 no.2
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• pp.1-27
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• 2007

This paper presents a fuzzy-goal programming(FGP) approach for Bi-Level Linear Multiple Objective Decision Making(BLL-MODM) problem in a large hierarchical decision making and planning organization. The proposed approach combines the attractive features of both fuzzy set theory and goal programming(GP) for MODM problem. The GP problem has been developed by fixing the weights and aspiration levels for generating pareto-optimal(satisfactory) solution at each level for BLL-MODM problem. The higher level decision maker(HLDM) provides the preferred values of decision vector under his control and bounds of his objective function to direct the lower level decision maker(LLDM) to search for his solution in the right direction. Illustrative numerical example is provided to demonstrate the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1245-1248
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• 1996

This paper describes a cell programming environment that deals with problems associated with programming Flexible Manufacturing Cells(FMCs). The environment consists of the cell programming editor and the automatic generation module. In the cell programming editor, cell programmers can develop cell programs using task level description set which supports task-oriented specifications for manipulation cell activities. This approach to cell programming reduces the amount of details that cell programmers need to consider and allows them to concentrate on the most important aspects of the task at hand. The automatic generation module is used to transform task specifications into executable programs used by cell constituents. This module is based on efficient algorithm and expert systems which can be used for optimal path planning of robot operations and optimal machining parameters of machine tool operations. The development tool in designing the environment is an object-oriented approach which provides a simple to use and intuitive user interface, and allows for an easy development of object models associated with the environment.

• Journal of Information Technology Applications and Management
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• v.23 no.2
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• pp.61-80
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• 2016

The wireless mesh network (WMN) is a next-generation technology for data networking that has the advantage in cost and the flexibility in its construction because of not requiring the infra-structure such as the ethernet. This paper focuses on the optimal link scheduling problem under the wireless mesh network to effectuate real-time streaming by using the constraint programming. In particular, Under the limitation of half-duplex transmission in wireless nodes, this paper proposes a solution method to minimize the makespan in scheduling packet transmission from wireless nodes to the gateway in a WMN with no packet transmission conflicts due to the half-duplex transmission. It discusses the conflicts in packet transmission and deduces the condition of feasible schedules, which defines the model for the constraint programming. Finally it comparatively shows and discusses the results using two constraint programming solvers, Gecode and the IBM ILOG CP solver.