• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.692-699
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• 2008

Semiconductor research and development(R&D) fabs are very different than production fabs in many ways such as the scales of production, job priority, production methods, and performance measures. Efficient operations of R&D fabs are very important to the development of new product, process stability, high yield, and ultimately company competitiveness. This paper proposes the fab-wide scheduling method for operational optimization of the R&D fabs. Most scheduling systems of semiconductor fabs have only focused on maximizing throughput of each separated areas without considering WIP(works in process) flows of entire fab. In this paper, we proposes the a fab-wide scheduling system which schedules all lots to entire fab equipment at once. We develop the MIP(mixed integer programing) model which allocates the lots to production equipment considering many constraints of all processes and the CP(constraint programming) model which determines the sequences of the lots in the production equipment. The proposed FAB-wide scheduling model is applied to the newly constructed R&D fab. As a result, we have accomplished the system based automated job reservation, decrease of the hot lot delay, increase of the queue time satisfaction, the high throughput by maximizing the batch sizes, decrease of the WIP TAT(Turn Around Time).

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.217-229
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• 2007

In this paper, Genetic Algorithm (GA) is used to find the Maximum Weight Independent Set (MWIS) of a graph. First, MWIS problem is formulated as a 0-1 integer programming optimization problem with linear objective function and a single quadratic constraint. Then GA is implemented with the help of this formulation. Since GA is a heuristic search method, exact solution is not reached in every run. Though the suboptimal solution obtained is very near to the exact one. Computational result comprising an average performance is also presented here.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.293-298
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• 2016

Document summarization is an important task in various areas where the goal is to select a few the most descriptive sentences from a given document as a succinct summary. Even without training data of human labeled summaries, there has been several interesting existing work in the literature that yields reasonable performance. In this paper, within the same unsupervised learning setup, we propose a more principled learning framework for the document summarization task. Specifically we formulate an optimization problem that expresses the requirements of both faithful preservation of the document contents and the summary length constraint. We circumvent the difficult integer programming originating from binary sentence selection via continuous relaxation and the low entropy penalization. We also suggest an efficient convex-concave optimization solver algorithm that guarantees to improve the original objective at every iteration. For several document datasets, we demonstrate that the proposed learning algorithm significantly outperforms the existing approaches.

• Asia pacific journal of information systems
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• v.6 no.2
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• pp.125-148
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• 1996

This paper is primarily focused on the function of model management systems such as higher level representations and buildings of optimization models using them, especially in the area of the telecommunication network models. This research attempts to provide the model builders an intuitive language-namely higher level representation-using five distinctivenesses : Objective, Node, Link, Topological Constraint including five components, and Decision. The paper elaborates all components included in each of distinctivenesses extracted from structural characteristics of typical telecommunication network models. Higher level representations represented with five distinctivenesses should be converted into base level representations which are employed for semantic representations of linear and integer programming problems in knowledge: assisted optimization modeling system(UNIK-OPT). Furthermore, for formulating the network model using higher level representations, the reasoning process is proposed. A system called UNIK-NET is developed to implement the approach proposed in this research, and the system is illustrated with an example of the network model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.715-722
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• 2005

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used products while satisfying the demand of their parts or components over a planning horizon. The case of single product type with assembly structure is considered for the objective of minimizing the sum of disassembly operation and inventory holding costs. In particular, the resource capacity constraint is explicitly considered. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To show the performance of the heuristic, computational experiments are done on a number of randomly generated problems, and the test results show that the algorithm can give near optimal solutions within a very short amount of computation time.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.1-9
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• 2005

This paper proposes the heuristic algorithm for the generalized GT problems to consider the restrictions which are given the number of machine cell and maximum number of machines in machine cell as well as minimum number of machines in machine cell. This approach is split into two phase. In the first phase, we use the similarity coefficient which proposes and calculates the similarity values about each pair of all machines and sort these values descending order. If we have a machine pair which has the largest similarity coefficient and adheres strictly to the constraint about birds of a different feather (BODF) in a machine cell, then we assign the machine to the machine cell. In the second phase, we assign parts into machine cell with the smallest number of exceptional elements. The results give a machine-part grouping. The proposed algorithm is compared to the Modified p-median model for machine-part grouping.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.1
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• pp.105-111
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• 2002

When transporting multiple items by trucks of various size, one needs to assign a group of items to each truck so as to minimize the total cost, while meeting the weight and volume constraint of each truck. In this paper, we formulate the problem as an integer programming problem and propose four heuristic algorithms for the problem. Computer simulation is used to evaluate the average performance of the four heuristic algorithms for the consolidated transportation problem.

• IE interfaces
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• v.17 no.spc
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• pp.69-78
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• 2004

This paper presents a simulated algorithm(SA) for the optimal reliability design problem of a series system with multiple component choices incorporated at each subsystem. The objective of the problem is to maximize the system reliability while satisfying some constraint on system budget. The problem is formulated as a nonlinear binary integer programming problem and characterized as an NP-hard problem. The SA algorithm is developed by introducing some solution-improvements methods. Numerical examples are tested and the results are compared. The results have demonstrated the efficiency and the effectiveness of the proposed SA algorithm.

• Korean Management Science Review
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• v.14 no.1
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• pp.205-227
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• 1997

Higher level representation splay an important role in model management systems. The role is to make decision makers friendly represent their problem using the representations. In this research, we address higher level representations including five distinctivenesses: Objective, Node, Link, Topological Constraint including five components, and Decision, Therefore, it is developed a system called HLRNET that implements the building procedure of network models using structural knowledge and object data The paper particularly elaborates all components included in each of distinctiveness extracted from structural characteristics of a lot of telecommunication network models. Higher level representations represented with five destinctivenesses should be converted into base level representations which are employed for semantic representations of linear and integer programming problems in a knowledge-assisted optimization modeling system. The system is illustrated with an example of the local access network model.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.401-405
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• 2004

Column subtraction, originally proposed by Harche and Thompson(]994), is an exact method for solving large set covering, packing and partitioning problems. Since the constraint set of ship scheduling problem(SSP) have a special structure, most instances of SSP can be solved by LP relaxation. This paper aims at applying the column subtraction method to solve SSP which can not be solved by LP relaxation. For remained instances of unsolvable ones, we subtract columns from the finale simplex table to get another integer solution in an iterative manner. Computational results having up to 10,000 0-1 variables show better performance of the column subtraction method solving the remained instances of SSP than complex branch-and-bound algorithm by LINDO.