• The KIPS Transactions:PartB
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• v.18B no.2
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• pp.73-82
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• 2011

There are a lot of people trying to solve the Traveling Salesman Problem (TSP) by using the Meta Heuristic Algorithms. TSP is an NP-Hard problem, and is used in testing search algorithms and optimization algorithms. Also TSP is one of the models of social problems. Many methods are proposed like Hybrid methods and Custom-built methods in Meta Heuristic. In this paper, we propose the S-MINE Algorithm to use the MINE Algorithm introduced in 2009 on the TSP.

• Korean Management Science Review
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• v.29 no.2
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• pp.143-155
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• 2012

The purpose of this study is to formulate and solve the scheduling problem to heat-treatment process in forging process and apply it to industries. Heat-treatment is a common process in manufacturing heavy forged products in ship engines and wind power generators. Total complete time of the schedule depends on how to group parts and assign them into heat furnace. Efficient operation of heat-treatment process increases the productivity of whole production system while scheduling the parts into heat-treatment furnace is a combinatorial problem which is known as an NP-hard problem. So the scheduling, on manufacturing site, relies on engineers' experience. To improve heat-treatment process schedule, this study formulated it into an MIP mathematical model which minimizes total complete time. Three methods were applied to example problems and the results were compared to each other. In case of small problems, optimal solutions were easily found. In case of big problems, feasible solutions were found and that feasible solutions were very close to lower bound of the solutions. ILOG OPL Studio 5.5 was used in this study.

• KIPS Transactions on Software and Data Engineering
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• v.4 no.5
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• pp.241-246
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• 2015

Although many different methods have been used to solve stereo correspondent problems, the deviation of accuracy is too big. Among those many methods, the one that uses segmentation information of input image has received high attention in academic field since it is very close to vision recognition. In this thesis, the existing method of acquiring a single value by using the segment information and initial disparity value was viewed in NP-hard problem to propose a new method. In order to verify the validity of the proposed method, well-known data were used for experiment and the resulted data was analyzed. Although there were some disadvantages in the time aspect, it showed somewhat useful results in the accuracy aspect.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1089-1095
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• 2004

The genetic algorithms have been used to take a near optimal solution because The generation of the optimal Steiner tree from a given network is NP-hard problem,. The chromosomes in genetic algorithm are represented with the floating point representation instead of the existing binary string for solving this problem. A spanning tree was obtained from a given network using Prim's algorithm. Then, the new Steiner point was computed using genetic algorithm with the chromosomes in the floating point representation, and it was added to the tree for approaching the result. After repeating these evolving steps, the near optimal Steiner tree was obtained. Using this method, the tree is quickly and exactly approached to the near optimal Steiner tree compared with the existing genetic algorithms using binary string.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.10
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• pp.562-574
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• 2004

We address the problem of energy-optimal voltage scheduling for fixed-priority hard real-time systems. First, we prove that the problem is NP-hard. Then, we present a fully polynomial time approximation scheme (FPTAS) for the problem. for any $\varepsilon$>0, the proposed approximation scheme computes a voltage schedule whose energy consumption is at most (1+$\varepsilon$) times that of the optimal voltage schedule. Furthermore, the running time of the proposed approximation scheme is bounded by a polynomial function of the number of input jobs and 1/$\varepsilon$. Experimental results show that the approximation scheme finds more efficient voltage schedules faster than the best existing heuristic.

• Management & Information Systems Review
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• v.34 no.2
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• pp.67-78
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• 2015

In this paper, we consider a scheduling problem of printed circuit board production process with setup cost depending job sequence. Given a set of PCBs, these are produced in single surface mounting device. The problem is to define job sequence with the objective of minimizing the total seutp cost. We propose a mathematical formulation and the problem is proven to be NP-hard. So, a meta heuristic based on genetic algorithm is developed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.4
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• pp.1-8
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• 2007

In some wireless sensor networks, the sensor nodes are required to be located sparsely at designated positions over a wide area, introducing the problem of adding minimum number of relay nodes to interconnect the sensor nodes. The problem finds its a bstract form in literature: the Minimum number of Steiner Points. Since it is known to be NP-hard, this paper proposes an approximation scheme to estimate the minimum number of relay nodes through the properties of the abstract form. Note that by reducing the numb er of nodes in a sensor network, the amount of data exchange over the net will be far decreased.

• Korean Management Science Review
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• v.25 no.1
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• pp.1-9
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• 2008

This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. This paper investigates the R&D project portfolio selection problem. Despite its importance and impact on real world projects, there exist few practical techniques that help construct an non-dominated portfolio for a decision makers satisfaction. One of the difficulties constructing the portfolio is that such project portfolio problem is, in nature, a multi-attribute decision-making problem, which is an NP-hard class problem. In order to obtain the non-dominated portfolio that a decision maker or a user is satisfied with, we devise a user-interface algorithm, in that the user provides the maximum/minimum input values for each project attribute. Then the system searches the non-dominated portfolio that satisfies all the given constraints if such a portfolio exists. The process that the user adjusts the maximum/minimum values on the basis of the portfolio found continues repeatedly until the user is optimally satisfied with. We illustrate the algorithm proposed, and the computational results show the efficacy of our procedure.

• Journal of KIISE:Software and Applications
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• v.32 no.8
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• pp.752-758
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• 2005

The transportation problem (TP) is known as one of the important problems in Industrial Engineering and Operational Research (IE/OR) and computer science. When the problem is associated with additional fixed cost for establishing the facilities or fulfilling the demand of customers, then it is called fixed charge transportation problem (fcTP). This problem is one of NP-hard problems which is difficult to solve it by traditional methods. This paper aims to show the application of spanning-tree based Genetic Algorithm (GA)approach for solving nonlinear fixed charge transportation problem. Our new idea lies on the GA representation that includes the feasibility criteria and repairing procedure for the chromosome. Several numerical experimental results are presented to show the effectiveness of the proposed method.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.317-326
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• 2007

We propose more enhanced heuristic for the GOSST(Grade of Services Steiner Minimum Tree) problem in this paper. GOSST problem is a variation of Steiner Tree problem and to find a network topology satisfying the G-Condition with minimum network construction cost. GOSST problem is known as one of NP-Hard or NP-Complete problems. In previous our research, we proposed a heuristic employing Direct Steiner Point Locating strategy with Distance Preferring MST building strategy. In this paper, we propose new Steiner point locating strategy, Zigzag Steiner point Locating strategy. Through the results of out experiments, we can assert this strategy is better than our previous works. The Distance Zigzag GOSST method which hires the Distance Preferring MST building strategy and Zigzag Steiner point Locating strategy defrays the least network construction cost and brings 31.5% cost saving by comparison to G-MST, the experimental control and 2.2% enhancement by comparison to the Distance Direct GOSST method, the best GOSST method in our previous research.