• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.109-117
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• 2022

Most of real-world decision-making processes are used to optimize problems with many objectives of conflicting. Since the betterment of some objectives requires the sacrifice of other objectives, different objectives may not be optimized simultaneously. Consequently, Pareto solution can be considered as candidates of a solution with respect to a multi-objective optimization (MOP). Such problem involves two main procedures: finding Pareto solutions and choosing one solution among them. So-called multi-objective genetic algorithms have been proved to be effective for finding many Pareto solutions. In this study, we suggest a fitness evaluation method based on the achievement level up to the target value to improve the solution search performance by the multi-objective genetic algorithm. Using numerical examples and benchmark problems, we compare the proposed method, which considers the achievement level, with conventional Pareto ranking methods. Based on the comparison, it is verified that the proposed method can generate a highly convergent and diverse solution set. Most of the existing multi-objective genetic algorithms mainly focus on finding solutions, however the ultimate aim of MOP is not to find the entire set of Pareto solutions, but to choose one solution among many obtained solutions. We further propose an interactive decision-making process based on a visualized trade-off analysis that incorporates the satisfaction of the decision maker. The findings of the study will serve as a reference to build a multi-objective decision-making support system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.485-488
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• 1998

Elementary school pupils frequently have difficult acquiring creative writing skills, i.e. how to develop the idea to be expressed, how to compose the materials of the outcome or contents. In this paper, we focus on the problems of how to support creative writing work to arrange materials in order to formulate ideas as the stories develop. the stories develop. The basic ideas behind the method are that(1) a basic story is automatically generated by GA-based operations and shown to a user as sequences of pictures, (2) IGA(Interactive Genetic Algorithm) is used to evaluate and select a preferred story, (3) the results are combined with previously stored stories using case-based techniques. Based on these ideas, we have developed a computer supported environment for this purpose and conducted related experiments.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.3
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• pp.332-340
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• 2016

A design optimization is performed for the double-bolted joint in cylindrical composite structures by using a simplified analytical method. This method uses failure criteria for the major failure modes of the bolted composite joint. For the double-bolted joint with a zigzag arrangement, it is necessary to consider an interaction effect between the bolt arrays. This paper proposes another failure mode which is determined by angle and distance between two bolts in different arrays and define a failure criterion for the failure mode. The optimal design for the double-bolted joint is carried out by considering the interactive net-tension failure mode. The genetic algorithm (GA) is adopted to determine the optimized parameters; bolt spacing, edge distance, and stacking sequence of the composite laminate. A purpose of the design optimization is to maximize the burst pressure of the cylindrical structures by ensuring structural integrity. Also, a progressive failure analysis (PFA) is performed to verify the results of the optimal design for the double-bolted joint. In PFA, Hashin 3D failure criterion is used to determine the ply that would fail. A stiffness reduction model is then used to reduce the stiffness of the failed ply for the corresponding failure mode.

• Journal of the Korea Society for Simulation
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• v.27 no.2
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• pp.101-114
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• 2018

Several different approaches and mechanisms are introduced to solve the UAV path planning problem. In this paper, we designed and implemented an agent-based simulation software using the Repast platform and Java Genetic Algorithm Package to examine an evolutionary path planning method by implementing and testing within the Repast environment. The paper demonstrates the life-cycle of an agent-based simulation software engineering project while providing a documentation strategy that allows specifying autonomous, adaptive, and interactive software entities in a Multi-Agent System. The study demonstrates how evolutionary path planning can be introduced to improve cognitive agent capabilities within an agent-based simulation environment.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.10
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• pp.1031-1036
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• 2015

Proportional-integral-derivative (PID) controllers are widely used in industrial sites. Most tuning methods for PID controllers use an empirical and experimental approach; thus, the experience and intuition of a designer greatly affect the tuning of the controller. The representative methods include the closed-loop tuning method of Ziegler-Nichols (Z-N), the C-C tuning method, and the Internal Model Control tuning method. There has been considerable research on the tuning of PID controllers for single-input single-output systems but very little for multi-input multi-output systems. It is more difficult to design PID controllers for multi-input multi-output systems than for single-input single-output systems because there are interactive control loops that affect each other. This paper presents a tuning method for the PID controller for a two-input two-output system. The proposed method uses a real-coded genetic algorithm (RCGA) as an optimization tool, which optimizes the PID controller parameters for minimizing the given objective function. Three types of objective functions are selected for the RCGA, and each PID controller parameter is determined accordingly. The performance of the proposed method is compared with that of the Z-N method, and the validity of the proposed method is examined.

• Korean Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.195-210
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• 1997

In Rapid Prototyping process, the time required to build multiple prototype parts can be reduced by packing several parts optimally in a work volume. Interactive arrangement of the multiple parts is a tedious process and does not guarantee the optimal placement of all the parts. In this case, packing is a kind of 3-D nesting problem because parts are represented by STL files with 3-D information. 3-D nesting is well known to be a problem requiring an intense computation and an efficient algorithm to solve the problem is still under investigation. This paper proposes that packing 3-D parts can be simplified into a 2-D irregular polygon nesting problem by using the characteristic of rapid prototyping process that the process uses 2-dimensional slicing data of the parts and that slice of the STL parts are composed of polygons. Our algorithm uses no-fit-polygon (NFP) to place each slice without overlapping other slices in the same z-level. The allowable position of one part at a fixed orientation for given parts already packed can be determined by obtaining the union of all NFP's that are obtained from each slice of the part. Genetic algorithm is used to determine the order of parts to be placed and orientations of each part for the optimal packing. Optimal orientation of a part is determined while rotating it about the axis normal to the slice by finite angles and flipping upside down. This algorithm can be applied to any rapid prototyping process that does not need support structures.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.3
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• pp.341-347
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• 2011

The redundancy allocation problem (RAP) is a famous NP.complete problem that has beenstudied in the system reliability area of ships and airplanes. Recently meta-heuristic techniques have been applied in this topic, for example, genetic algorithms, simulated annealing and tabu search. In particular, tabu search (TS) has emerged as an efficient algorithmic approach for the series-parallel RAP. However, the quality of solutions found by TS depends on the initial solution. As a robust and efficient methodology for the series-parallel RAP, the hybrid metaheuristic (TSA) that is a interactive procedure between the TS and SA (simulated annealing) is developed in this paper. In the proposed algorithm, SA is used to find the diversified promising solutions so that TS can re-intensify search for the solutions obtained by the SA. We test the proposed TSA by the existing problems and compare it with the SA and TS algorithm. Computational results show that the TSA algorithm finds the global optimal solutions for all cases and outperforms the existing TS and SA in cases of 42 and 56 subsystems.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.116-118
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• 1999

일반적으로 컴퓨터를 이용한 디자인 지원 시스템은 많은 양의 수집된 데이터에 기반하기 때문에 계속해서 변화하는 유행에 대처할 수 없을 뿐만 아니라 개인의 취향을 반영하기도 어렵다. 이같은 문제점을 해결하기 위해 이 논문에서는 대화형 유전자 알고리즘(Interactive Genetic Algorithm : IGA)을 이용한 디자인 지원 시스템을 제안한다. IGA는 상호작용에서 얻어지는 사용자의 평가를 적합도 함수로 사용하는 유전자 알고리즘의 하나로, 일반적인 적합도 함수를 결정하기 어려운 디자인이나 예술 등의 문제 해결에 사용될 수 있다. 이때, 몇 개의 부분적인 곡선으로 의상의 디자인을 표현하였던 기존의 방법들과는 달리 전체 디자인을 목과 몸통, 팔과 소매, 치마와 허리선의 세 가지 부분 디자인으로 나누어 표현하는 문제영역 지식을 활용함으로써 좀 더 현실적인 여성복을 디자인할 수 있었다. 시스템의 인터페이스를 보완하기 위해 OpenGL이 사용되었으며, 실험 결과 지식기반 인코딩을 통한 IGA 의상디자인 시스템이 유용함을 알 수 있었다.

• Journal of KIISE:Software and Applications
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• v.27 no.9
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• pp.942-951
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• 2000

일반적으로 컴퓨터를 이용한 디자인 지원 시스템은 다지이너의 행동과 같은 데이터를 통계적으로 분석하여 일련의 디자인 행위를 추출해 내는 인공지능의 접근 방식을 사용하여 왔다. 그러나 이는 많은 양의 수집된 데이터를 기반한 방법이기 때문에 계속해서 변화하는 유행에 대처할 수 없을 뿐만 아니라 개인의 취향을 반영하기도 어렵다. 이같은 문제점을 해결하기 위해 이 논문에서는 대화형 유전자 알고리즘(Interactive Genetic Algorithm : IGA)을 이용하여 명시적으로 표현하기 어려운 취향을 적절히 반영하는 디자인 지원 시스템을 제안한다. IGA는 상호작용에서 얻어지는 사용자의 평가를 적합도 함수로 사용하는 유전자 알고리즘의 하나로, 일반적인 적합도 함수를 결정하기 어려운 디자인이나 예술 등의 문제 해결에 사용될 수 있다. 한편, 몇 개의 부분적인 곡선으로 의상의 디자인을 표현하였던 기존의 방법들과는 달리 전체 디자인을 목과 몸통, 팔과 소매, 치마와 허리선의 세 가지 부분 디자인으로 나누어 표현함으로써 좀더 현실적인 여성복을 디자인할 수 있었다. 시스템의 인터페이스를 보완하기 위해 OpenGL을 이용한 3차원 모델이 사용되었으며, 사용자들을 대상으로 한 실험 결과 제안한 의상 디자인 지원 시스템이 효과적임을 알 수 있었다.

• Journal of KIISE:Software and Applications
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• v.26 no.3
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• pp.422-430
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• 1999

멀티미디어 영상검색 중 영상의 내용을 기반으로 한 검색방법에 관한 연구가 활발히 진행되고 있다. 이는 기존의 키워드기반 영상검색 방법에 비해 효율적인 관리와 검색 방법을 제공하고 있다. 그러나 대부분의 방법이 단순한 공학적 방법에 치우쳐 사람의 감성과는 무관한 검색 결과를 제공한다. 이러한 문제점을 해결하기 위해 본 논문에서는 대화형 유전자 알고리즘을 도입하여 검색과정에 사람의 감성을 반영할 수 있는 방법을 제안한다. 이 방법은 구체적으로 표현될 수 있는 영상 뿐 아니라 우울한 느낌의 영상, 즐거운 느낌의 영상과 같은 추상적인 느낌의 영상을 검색할수 있도록 한다. 2000개의 영상으로 이루어진 데이터베이스로 실험한 결과 , 제안한 방법이 유용함을 알 수 있었다.