• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.8
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• pp.1981-1986
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• 2014

The problem studied in this paper is the channel routing problem to assign points with p colors on the upper row of the channel to points on the lower row in order to minimize its density. The case that the points on the upper row has an identical color or only two colors is studied in [1, 2]. This paper generalizes that to the points with p colors. First, we consider the problem to determine whether there is an assignment with density less than or equal to d, when an arbitrary d is given. We show that the problem is solved in O(p(n+m)log(n+m)) time. Using this result, we resolve the problem to fine an assignment with a minimum density.

• Journal of Ubiquitous Convergence Technology
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• v.2 no.1
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• pp.40-50
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• 2008

The problem of assigning customers to satellite channels is a difficult combinatorial optimization problem and is NP-complete. For this combinatorial optimization problem, standard optimization methods take a large computation time and so genetic algorithms (GA) and ant colony optimization (ACO) can be used to obtain the best and/or optimal assignment of customers to satellite channels. In this paper, we present a comparative study of GA and ACO to this problem. Various issues related to genetic algorithms approach to this problem, such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. We also discuss an ACO for this problem. In ACO methodology, three strategies, ACO with only ranking, ACO with only max-min ant system (MMAS), and ACO with both ranking and MMAS, are considered. A comparison of these two approaches (i,e., GA and ACO) with the standard optimization method is presented to show the advantages of these approaches in terms of computation time.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.141-151
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• 2012

This paper suggests more simple algorithm than Hungarian algorithm for assignment problem. Hungarian algorithm selects minimum cost of row and column, and subtracts minimum cost from each cost. Then, performs until the number of minimum lines with 0 equals the number of rows. But, the proposed algorithm selects the minimum cost for each rows only. From the start point with over 2 to the target point with null selects in column, fixes the maximum opportunity cost that the difference of the cost of starting point and target point, and moves the cost less than opportunity cost th more than previous cost. For the 25 balance and 7 unbalance assignment problems, This algorithm gets the optimal solution same as Hungarian algorithm. This algorithm improves the time complexity $O(n^3)$ of Hungarian algorithm to $O(n^2)$, and do not performs the transformation process from unbalance to balance assignment in Hungarian algorithm. Therefore, this algorithm can be alter Hungarian algorithm in assignment problem.

• ETRI Journal
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• v.29 no.3
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• pp.329-335
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• 2007

This paper considers a timeslot assignment problem in an interactive satellite multimedia (ISM) system with digital video broadcast-return channel via satellite (DVB-RCS). The timeslot assignment problem is formulated as a binary integer programming to maximize the overall weighted throughput and is shown to be NP-hard. Thus, three real-time heuristic algorithms including ratio-based, packet-size (PS)-based, and transmission gain (TG)-based are derived, and some computational experiments are made. Considering the results, the ratio-based heuristic algorithm is demonstrated to be the most effective and efficient. We propose adapting the ratio-based heuristic algorithm to the timeslot assignment problem to greatly improve the ISM system utilization.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.65-75
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• 2008

Over the last three decades, there are many researches focusing on the practice and theory of RM in airlines. Most of them have dealt with a seat assignment problem for maximizing the total revenue. In this study, we focus on a seat assignment problem in airlines. The seat assignment problem can be modeled as a stochastic programming model which is difficulty to solve optimally. However, with some assumptions on the demand distribution functions and a linear approximation technique, we can transform the complex stochastic programming model to a Linear Programming model. Some computational experiments are performed to evaluate out model with randomly generated data. They show that our model has a good performance comparing to existing models, and can be considered as a basis for further studies on improving existing seat assignment models.

• Communications of the Korean Mathematical Society
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• v.17 no.2
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• pp.321-330
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• 2002

Consider the random assignment (or bipartite matching) problem with iid uniform edge costs t(i, j). Let $A_{n}$ be the optimal assignment cost. Just recently does Aldous [2] give a rigorous proof that E $A_{n}$ longrightarrowζ(2). In this paper we establish the upper and lower bounds for Var $A_{n}$ , i.e., there exist two strictly positive but finite constants $C_1$ and $C_2$ such athat $C_1$ $n^{(-5}$2)/ (log n)$^{(-3}$2)/ $\leq$ Var $A_{n}$ $\leq$ $C_2$ $n^{-1}$ (log n)$^2$.EX>.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.2
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• pp.129-140
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• 2009

This paper introduces the planar storage location assignment problem (PSLAP) that no research has attempted to mathematically solve. The PSLAP can be defined as the assignment of the inbound and outbound objects to the storage yard with aim of minimizing the number of obstructive object moves. The storage yard allows only planar moves of objects. The PSLAP usually occurs in the assembly block stockyard operations at a shipyard. This paper formulates the PSLAP using a mathematical programming model, but which belongs to the NP-hard problems category. Thus this paper utilizes an efficient genetic algorithm (GA) to solve the PSLAP for real-sized instances. The performance of the proposed mathematical programming model and developed GA is verified by a number of numerical experiments.

• Korean Management Science Review
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• v.26 no.3
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• pp.117-131
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• 2009

Over the last three decades, there are many researches focusing on the practice and theory of RM in airlines. Most of them have dealt with a seat assignment problem for maximizing the total revenue. In this study, we focus on a seat assignment problem in airlines. The seat assignment problem can be modeled as a stochastic programming model which is difficulty to solve optimally. However, with some assumptions on the demand distribution functions and a linear approximation technique, we can transform the complex stochastic programming model to a Linear Programming model. Some computational experiments are performed to evaluate out model with randomly generated data. They show that our model has a good performance comparing to existing models, and can be considered as a basis for further studies on improving existing seat assignment models.

• International Journal of Control, Automation, and Systems
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• v.4 no.5
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• pp.653-659
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• 2006

The design of $H_2$-optimal control with regional pole assignment via state feedback in linear time-invariant systems is investigated. The aim is to find a state feedback controller such that the closed-loop system has the desired eigenvalues lying in some desired stable regions and attenuates the disturbance between the output vector and the disturbance vector. Based on a proposed result of parametric eigenstructure assignment via state feedback in linear systems, the considered $H_2$-optimal control problem is changed into a minimization problem with certain constraints, and a simple and effective algorithm is proposed for this considered problem. A numerical example and its simulation results show the simplicity and effectiveness of this proposed algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.133-141
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• 1987

Man-machine assignment problem with random service and processing times is considered in this paper. Assuming heterogeneous semi-automatic machines, the problem is dealt with as follow; 1. For the different type of machines that have probabilistics distribution of processing time and nan service time, man·machine assignment problem is solved by heuristic method using expected time value if machine. 2. Since each related time is a random variable, the performance of the optimal assignment obtained from the above method is verified through monte carlo simulation method. 3. The above procedures are programed by BASIC language to use easily and rapidly in the personal computer. The result of this study can contribute to productivity enhancement by increasing the efficiencies of both operators and machines.