• 접착 및 계면
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• 제10권3호
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• pp.127-133
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• 2009

아크릴 점착제는 고내구성 및 분자량 조절, 관능기의 도입 등이 용이하여 반도체, 디스플레이, 모바일 기기, 자동차 등의 첨단 산업에서 매우 다양하게 활용되고 있다. 점착제의 점착물성은 산업에서의 적용, 공정관리, 제품의 신뢰성에 지대한 영향을 미치기에 그 중요성이 날로 더해가고 있다. 본 연구에서는 조합기법을 이용하여 아크릴 점착제의 물성 영향인자 가운데 두께의 변화에 따른 점착물성 변화를 살펴보고자 한다. 아크릴 점착제는 2-ethylhexyl acrylate와 acrylic acid로 구성된 기본점착제만을 활용하여 샘플을 제작하였으며, 두께 구배가 가능한 micro applicator를 활용하여 thickness-gradient acrylic PSA 샘플을 제작하였으며, 이를 기존의 코팅법으로 제작한 샘플과 비교함으로써 조합기법의 재현성을 평가하였다.

• International Journal of Control, Automation, and Systems
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• 제6권4호
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• pp.468-476
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• 2008

This paper presents a novel approach to economic dispatch (ED) with nonconvex fuel cost function as combinatorial optimization problems (COP) while most of the conventional researches have been developed as function optimization problems (FOP). One nonconvex fuel cost function can be divided into several convex fuel cost functions, and each convex function can be regarded as a generation type (G-type). In that case, ED with nonconvex fuel cost function can be considered as COP finding the best case among all feasible combinations of G-types. In this paper, a genetic algorithm is applied to solve the COP, and the $\lambda$-P table method is used to calculate ED for the fitness function of GA. The $\lambda$-P table method is reviewed briefly and the GA procedure for COP is explained in detail. This paper deals with three kinds of ED problems, namely ED considering valve-point effects (EDVP), ED with multiple fuel units (EDMF), and ED with prohibited operating zones (EDPOZ). The proposed method is tested for all three ED problems, and the test results show an improvement in solution cost compared to the results obtained from conventional algorithms.

• 품질경영학회지
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• 제18권1호
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• pp.48-54
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• 1990

The purpose of this study is to design effective working systems which adapt to change in human needs by developing an method which forms into optimal groups using the measure of cohesion. Two main results can be derived from the study as follows : First, the clustering method based on the entropic measure of cohesion is predominant with respect to any other methods proposed in designing the work groups, since this clustering criterion includes symmetrical relations of total work groups and the dissimilarity as well as the similarity relations of predicate value, the clustering method based on this criterion is suitable for designing the new work structure. Second, total work group is clustered as the workers who have the equal predicate value and then clustering results are produced through the combinatorial agglomerative hierarchical clustering method. This clustering method present more economic results than the method that clustering the total work group do.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2004년도 Asia Display / IMID 04
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• pp.647-649
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• 2004

We have synthesized phosphor in the system CaO-$Al_2O_3-SiO_2$ by combinatorial polymerized-complex method. The application of combinatorial synthesis and characterization of luminescent materials has been enlarged to identification and optimization in interesting new phosphor. In this study, we investigated luminescent properties of above-mentioned materials by excitation and emission spectra. In $Eu^{2+}$ activated $Ca_1Al_2Si_2O_8$ phosphor emit the blue light.

• 한국경영과학회지
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• 제29권4호
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• pp.117-134
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• 2004

This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

• 한국경영과학회지
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• 제21권2호
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• pp.125-140
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• 1996

Simulated annealing (SA) is a very promising general purpose algorithm which can be conveniently utilized for various complicated combinatorial optimization problems. But its slowness has been pointed as a major drawback. In this paper, we propose an accelerated SA and test its performance experimentally by applying it for two standard combinatorial optimization problems (TSP(Travelling Salesman Problem) and GPP(Graph Partitioning Problem) of various sizes. It turns out that performance of the proposed method is consistently better both in convergenge speed and the quality of solution than the conventional SA or SE (Stochastic Evolution). In the second part of the paper we apply the accelerated SA to solve the virtual path management problem encountered in ATM netowrks. The problem is modeled as a combinatorial optimization problem to optimize the utilizy of links and an efficient SA implementation scheme is proposed. Two application examples are given to demonstrate the validity of the proposed algorithm.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2004년도 추계학술대회
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• pp.171-178
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• 2004

This study suggests a general paradigm enhancing genetic mutability. Mutability among heterogeneous members in a genetic population has been a major problem in application of genetic programming to diverse business problems. This suggested paradigm is implemented to developing new methods from existing methods. Within the evolutionary approach taken to designing new methods, a general representation scheme of the genetic programming framework, called a kernel, is introduced. The kernel is derived from the literature of algorithms and heuristics for combinatorial optimization problems. The commonality and differences among these methods have been identified and again combined by following the genetic inheritance merging them. The kernel was tested for selected methods in combinatorial optimization. It not only duplicates the methods in the literature, it also confirms that each of the possible solutions from the genetic mutation is in a valid form, a running program. This evolutionary method suggests diverse hybrid methods in the form of complete programs through evolutionary processes. It finally summarizes its findings from genetic simulation with insight.

• 제어로봇시스템학회논문지
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• 제21권7호
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• pp.699-708
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• 2015

In the testing of a software component-based robot system, generating test cases for the system is a time-consuming and difficult task that requires the combining of test data. This paper proposes an adaptive combinatorial testing method which is based on the input/output relationship among components and which automatically generates the test cases for the system. The proposed algorithm first generates an input/output relationship graph in order to analyze the input/output relationship of the system. It then generates the reduced set of test cases according to the analyzed type of input/output relationship. To validate the proposed algorithm some comparisons are given in terms of the time complexity and the number of test cases.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.143-146
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• 1996

In this paper, we propose a hopfield model for solving the part-matching which is the number of parts and positions are changed. The goal of this paper is to minimize part-connection in pairs and net total path of part-connection. Therefore, this kind of problem is referred to as a combinatorial optimization problem. First of all, we review the theoretical basis for hopfield model to optimization and present two method of part-matching; Traveling Salesman Problem (TSP) and Weighted Matching Problem (WMP). Finally, we show demonstration through computer simulation and analyzes the stability and feasibility of the generated solutions for the proposed connection methods.

• 대한수학회보
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• 제53권5호
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• pp.1281-1289
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• 2016

Richard Stanley suggested the problem of finding combinatorial proofs of formulas for counting regions of certain hyperplane arrangements defined by hyperplanes of the form $x_i=0$, $x_i=x_j$, and $x_i=2x_j$ that were found using the finite field method. We give such proofs, using embroidered permutations and linear extensions of posets.