• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.179-184
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• 2002

We consider the heterogeneous fleet vehicle routing problem (HVRP), a variant of the classical vehicle routing problem (VRP). The HVRP differs from the classical VRP in that it deals with a heterogeneous fleet of vehicles having various capacities, fixed costs, and variables costs. Therefore the HVRP is to find the fleet composition and a set of routes with minimum total cost. We give an integer programming formulation of the problem and propose an algorithm to solve it. Although the formulation has exponentially many variables, we can efficiently solve the linear programming relaxation of it by using the column generation technique. To generate profitable columns we solve a shortest path problem with capacity constraints using dynamic programming. After solving the linear programming relaxation, we apply a branch-and-bound procedure. We test the proposed algorithm on a set of benchmark instances. Test results show that the algorithm gives best-known solutions to almost all instances.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.5
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• pp.266-274
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• 2004

This paper presents a scheme for the interconnection of dispersed generator systems(DGs) based on load .unbalance and load model in composite distribution systems. Groups of each individual load model consist of residential, industrial, commercial, official and agricultural load. The unbalance is involved with many single-phase line segment. . Voltage profile improvement and system loss minimization by installation of DGs depend greatly on how they are placed and operated in the distribution systems. So, DGs can reduce distribution real power losses and replace large-scale generators if they are placed appropriately in the distribution systems. The main idea of solving fuzzy goal programming is to transform the original objective function and constraints into the equivalent multi-objectives functions with fuzzy sets to evaluate their imprecise nature for the criterion of power loss minimization, the number or total capacity of DGs and the bus voltage deviation, and then solve the problem using genetic algorithm. The method proposed is applied to IEEE 13 bus and 34 bus test systems to demonstrate its effectiveness.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.1-8
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• 2013

Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and -9.57%~9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within ${\pm}10%$.

• ETRI Journal
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• v.36 no.4
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• pp.686-689
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• 2014

This paper studies energy-efficiency (EE) power allocation for cognitive radio MIMO-OFDM systems. Our aim is to minimize energy efficiency, measured by "Joule per bit" metric, while maintaining the minimal rate requirement of a secondary user under a total power constraint and mutual interference power constraints. However, since the formulated EE problem in this paper is non-convex, it is difficult to solve directly in general. To make it solvable, firstly we transform the original problem into an equivalent convex optimization problem via fractional programming. Then, the equivalent convex optimization problem is solved by a sequential quadratic programming algorithm. Finally, a new iterative energy-efficiency power allocation algorithm is presented. Numerical results show that the proposed method can obtain better EE performance than the maximizing capacity algorithm.

• International Journal of Railway
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• v.2 no.3
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• pp.99-106
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• 2009

Checks and tests before putting safety facilities into service as well as the results of these tests are essential, time consuming and may show great variations between each other. Economic constraints and the increasing complexity associated with the development of computerized tools tend to limit the capacity of the classic approval process (manual or automatic). A reduction of the validation cover rate could result in practice. This is not compatible with the French national plan to renew the interlocking systems of the national network. The method and the tool presented in this paper makes it possible to formally validate new computerized systems or evolutions of existing French interlocking systems with real-time functional interpreted Petri nets. The aim of our project is to provide SNCF with a method for the formal validation of French interlocking systems. A formal proof method by assertion, which is applicable to industrial automation equipment such as interlocking systems, and which covers equally the specification and its real software implementation, is presented in this paper. With the proposed method we completely verify that the system follows all safety properties at all times and does not show superfluous conditions: it replaces all the indoor checks (not the outdoor checks). The advantages expected are a significant reduction of testing time and of the related costs, an increase of the test coverage rate, an answer to the new demand of railway infrastructure maintenance engineering to modify and validate computerized interlocking systems. Formal methods mastery by infrastructure engineers are surely a key to prove that more safety is not necessarily more expensive.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.3
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• pp.234-240
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• 1999

This paper presents a new approach for large-scale generator maintenance scheduling optimizations. The generator preventive maintenance scheduling problems are typical discrete dynamic n-dimensional vector optimization ones with several inequality constraints. The considered objective function to be minimized a subset of{{{{ { R}^{n } }}}} space is the variance (i.g., second-order momentum) of operating reserve margin to levelize risk or reliability during a year. By its nature of the objective function, the optimal solution can only be obtained by enumerating all combinatorial states of each variable, a task which leads to computational explosion in real-world maintenance scheduling problems. This paper proposes a new priority search mechanism based on each generator's discrete sensitivity value which was analytically developed in this study. Unlike the conventional capacity-based priority search, it can prevent the local optimal trap to some extents since it changes dynamically the search tree in each iteration. The proposed method have been applied to two test systems (i.g., one is a sample system with 10 generators and the other is a real-world lage scale power system with 280 generators), and the results anre compared with those of the conventional capacith-based search method and combinatorial optimization method to show the efficiency and effectiveness of the algorithm.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.423-432
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• 2014

Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is applied for solving Combined Economic Emission Dispatch (CEED) problem with valve-point loading of thermal generators. This CEED problem with valve-point loading is a nonlinear, constrained multi-objective optimization problem, with power balance and generator capacity constraints. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a nonsmooth optimization problem. To validate its effectiveness of NSGA-II, two benchmark test systems, IEEE 30-bus and IEEE 118-bus systems are considered. To compare the Pareto-front obtained using NSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Comparison with other optimization techniques showed the superiority of the NSGA-II approach and confirmed its potential for solving the CEED problem. Numerical results show that NSGA-II algorithm can provide Pareto-front in a single run with good diversity and convergence. An approach based on Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is applied on non-dominated solutions obtained to determine Best Compromise Solution (BCS).

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.429-430
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• 2007

The enlargement of an electric power system network gives us much challenges concerning with network operation. In addition to it, the fast aging process of network equipments requires more chance to check and maintenance, and also the increase of heavy loaded facilities and the increase of the fault current in the network need to exchange with the larger facilities in capacity. Due to these reasons, outages trend to increase. Network solution studies for outages are performed mainly for two purposes. The first one is to find the countermeasures when the outage causes a violation of the network reliability criteria. And the second one is to minimize network constraints due to outages. There are so many outages around 400 for only one month. Therefore, in order to do case studies for outage, not only skilled persons are needed, but also many available tools to help properly. Concerning with proper tools, we will introduce a program which we developed to get informations concerned with network sensitivity, and an example to apply that program.

• Journal of the Korean Society of Propulsion Engineers
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• v.2 no.1
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• pp.88-94
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• 1998

Installation design methods and results of an aircraft engine on the wing-mounted-nacelle type aircraft has been presented in this paper. The design process starts from design requirements and constraints and covers some major aspects of the engine installation design such as wing-nacelle interference drag, roll clearance, ground clearance, nose gear collapse margin, rotor burst and fuel tank capacity. The method was applied to 100-seat class airplane(K100). Results of the design suggest optimum nacelle location and nacelle installation angle(toe-in, incidence, droop angle) which satisfies in stalled engine performance and size/location of wing dry day.

• Structural Engineering and Mechanics
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• v.59 no.5
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• pp.933-950
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• 2016

Decks, interior beams, edge beams and girders are the parts of a steel floor system. If the deck is optimized without considering beam optimization, finding best result is simple. However, a deck with higher cost may increase the composite action of the beams and decrease the beam cost reducing the total cost. Also different number of floor divisions can improve the total floor cost. Increasing beam capacity by using castellated beams is other efficient method to save the costs. In this study, floor optimization is performed and these three issues are discussed. Floor division number and deck sections are some of the variables. Also for each beam, profile section of the beam, beam cutting depth, cutting angle, spacing between holes and number of filled holes at the ends of castellated beams are other variables. Constraints include the application of stress, stability, deflection and vibration limitations according to the load and resistance factor (LRFD) design. Objective function is the total cost of the floor consisting of the steel profile cost, cutting and welding cost, concrete cost, steel deck cost, shear stud cost and construction costs. Optimization is performed by enhanced colliding body optimization (ECBO), Results show that using castellated beams, selecting a deck with higher price and considering different number of floor divisions can decrease the total cost of the floor.