• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.166-175
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• 1995

When a neutral particle beam(NPB) aimed at the object and receive a small number of neutron signals at the detector without any errors, it obeys Poisson law. Under the two assumptions that neutral particle scattering distribution and aiming errors have a circular Gaussian distributions that neutral particle scattering distribution and aiming errors have a circular Gaussian distribution respectively, an exact probability distribution of neutral particles vecomes a Poisson-power function distribution. We study and prove some properties, such as limiting distribution, unimodality, stochastical ordering, computational recursion fornula, of this distribution. We also prove monotone likelihood ratio(MLR) property of this distribution. Its MLR property can be used to find a criteria for the hypothesis testing problem.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.1
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• pp.92-100
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• 2009

Today international trade through maritime transportation is significantly increasing. Due to this increase, shipping companies are faced with problems concerning the repositioning of empty containers from import dominant ports. The liner shipping service network has been provided to transport containers which load customers' freights. Container ships are moved on the liner shipping service network by observing the predetermined route and transportation time. This research deals with the empty containers distribution problem considering the container ship route. A mathematical model based on the mixed integer program has been introduced in this study. The objective is to minimize the total relevant costs of empty containers such as handling, leasing, and inventory holding, etc. Due to the complexity of the problem, a genetic algorithm has been suggested to solve large sized problems within a reasonable time. Numerical experiments have been conducted to show the efficiency of the genetic algorithm.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.5
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• pp.217-224
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• 2002

This paper presents an algorithm to obtain an approximate optimal solution for the service restoration and load balancing of large scale radial distribution system in a real-time operation environment. Since the problem is formulated as a combinatorial optimization problem, it is difficult to solve a large-scale combinatorial optimization problem accurately within the reasonable computation time. Therefore, in order to find an approximate optimal solution quickly, the authors proposed an algorithm which combines optimization technique called cyclic best-first search with heuristic based feeder loadings balance index for computational efficiency and robust performance. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the KEPCO's 108 bus distribution system.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.501-506
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• 1993

An efficient solution algorithm of the optimal load distribution problem with joint torque constraints is presented. Multiple robot system where each robot is rigidly grasping a common object is considered. The optimality criteria used is the sum of weighted norm of the joint torque vectors. The maximum and minimum bounds of each joint torque in arbitrary form are considered as constraints, and the solution that reduces the internal force to zero is obtained. The optimal load distribution problem is formulated as a quadratic optimization problem in R, where I is the number of robots. The general solution can be obtained using any efficient numerial method for quadratic programming, and for dual robot case, the optimal solution is given in a simple analytical form.

• Korean Management Science Review
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• v.29 no.2
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• pp.21-34
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• 2012

This paper addresses a network design problem in a supply chain system that involves locating both plants and distribution centers, and determining the best strategy for distributing products from the suppliers to the plants, from the plants to the distribution centers and from the distribution centers to the customers. This paper suggests a cooperative coevolutionary algorithm (CCEA) approach to solve the model. First, the problem is decomposed into three subproblems for each of which the chromosome population is created correspondingly. Each chromosome in each population is represented as a permutation denoting the priority. Then an algorithm generating a solution from the combined set of chromosomes from each population is suggested. Also an algorithm evaluating the performance of a solution is suggested. An experimental study is carried out. The results show that our CCEA tends to generate better solutions than the previous CCEA as the problem size gets larger and that the permutation representation for chromosome used here is better than other representation.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.137-141
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• 2000

This paper presents an application of a new Adaptive Genetic Algorithms(AGA) to solve the Optimal Routing problem(ORP) for distribution system planning. In general, since the ORP is modeled as a mixed integer problem with some various mathematical constraints, it is hard to solve the problem. In this paper, we proposed a new adaptive strategy in GA to overcome the premature convergence and improve the convergence efficiency. And for these purposes, we proposed a fitness function suited for the ORP. In the proposed AGA, we used specially designed adaptive probabilities for genetic operators to consider the characteristics of distribution systems that are operated under radial configuration. The proposed algorithm has been tested in sample networks and the results are presented.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.533-535
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• 2002

In Korea, power requirement has been increasing. But the large generation unit is hardly installed because of economic and environment problem. Therefore, the concern of dispersed generation system(DGS) is growing. The power distribution system is generally operated with radial type. The protection system is composed of one directive source. But power distribution system inserted DGS changes it to two directive source system. Therefore, the insertion of DGS has the problem of protection coordination. In this paper, we argue fault current affected by interconnected DGS. We analyze fault current flow affected by DGS placement. Then, we find protective coordination problem. Consequently, we study advance point for protection scheme of power system interconnected DGS.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.127-129
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• 2002

This paper presents a fuzzy-GA method to resolve dispersed generator placement for distribution systems. The problem formulation considers an objective to reduce power loss costs of distribution systems and the constraints with the number or size of dispersed generators and the deviation of the bus voltage. The main idea of solving fuzzy nonlinear 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 and solve the problem using the proposed genetic algorithm, without any transformation for this nonlinear problem to a linear model or other methods. The method proposed is applied to the sample systems to demonstrate its effectiveness.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.71-73
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• 1995

This paper presents an optimization technique using genetic algorithms(GA) for loss minimization in the distribution network reconfiguration. Determining switch position to be opened for loss minimization in the radial distribution system is a discrete optimization problem. GA is appropriate to solve the multivariable optimization problem and it uses population, not a solution. For this reason, GA is attractive to solve this problem. In this paper, we aimed at finding appropriate open sectionalizing switch position using GA, which can lead to minimum transmission losses.

• Management Science and Financial Engineering
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• v.17 no.2
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• pp.1-21
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• 2011

This paper considers an integrated inventory-distribution system with a fleet of heterogeneous vehicles employed where a single warehouse distributes a single type of products to many spatially distributed retailers to satisfy their dynamic demands. The problem is to determine order planning at the warehouse, and also vehicle schedules and delivery quantities for the retailers with the objective of minimizing the sum of ordering cost at the warehouse, inventory holding cost at both the warehouse and retailers, and transportation cost. For the problem, we give a Mixed Integer Programming formulation and develop a Lagrangean heuristic procedure for computing lower and upper bounds on the optimal solution value. The Lagrangean dual problem of finding the best Lagrangrean lower bound is solved by subgradient optimization. Computational experiments on randomly generated test problems showed that the suggested algorithm gives relatively good solutions in a reasonable amount of computation time.