• Annual Conference of KIPS
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• 2023.05a
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• pp.18-19
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• 2023

최근 상품의 특성을 고려하지 않은 박스 크기 선택과 박스 공간 내 비효율적인 상품 배치로 인하여 박스의 파손 문제가 지속적으로 제기되고 있다. 이는 적재하고자 하는 상품의 특성을 고려하지 않고 상품을 대략적으로 배치하기 때문이다. 따라서 본 논문에서는 면적과 무게와 같은 상품의 특성을 고려한 상품 배치 최적화 알고리즘을 제안하여 공간 배치의 비효율성 문제를 최소화하고자 한다. 제안한 상품 배치 최적화 알고리즘은 검색 트리 (search tree)와 상품 특성 기반 평가 함수(evaluation function)로 구성되어 있다. 상품 특성 기반 평가 함수는 면적, 무게 및 바닥에 닿는 면적을 고려하여 설계되었다.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.829-839
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• 2004

Methods based on integer programming have been shown to be very effective in solving various crew pairing optimization problems. However, their applicability is limited to problems with linear constraints and objective functions. Also, those methods often require an unacceptable amount of time and/or memory resources given problems of larger scale. Heuristic methods such as neighborhood search, on the other hand, can handle large-scaled problems without too much difficulty and can be applied to problems having any form of objective functions and constraints. However, neighborhood search often gets stuck at local optima when faced with complex search spaces. This paper presents ,i hybrid algorithm of neighborhood search and integer programming, which nicely combines the advantages of both methods. The hybrid algorithm has been successfully tested on a large-scaled crew pairing optimization problem for a real subway line.

• Journal of the Korea Society of Computer and Information
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• v.10 no.5 s.37
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• pp.179-186
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• 2005

This paper describes a genetic algorithm and compares three crossover operators for Rural Postman Problem with Time Windows (RPPTW). The RPPTW which is a multiobjective optimization problem, is an extension of Rural Postman Problem(RPP) in which some service places (located at edge) require service time windows that consist of earliest time and latest time. Hence, RPM is a m띤tieect optimization Problem that has minimal routing cost being serviced within the given time at each service Place. To solve the RPPTW which is a multiobjective optimization problem, we obtain a Pareto-optimal set that the superiority of each objective can not be compared. This Paper performs experiments using three crossovers for 12 randomly generated test problems and compares the results. The crossovers using in this Paper are Partially Matched Exchange(PMX) Order Exchange(OX), and Modified Order Exchange(MOX) which is proposed in this paper. For each test problem, the results show the efficacy of MOX method for RPPTW.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.751-756
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• 2003

Ant Colony Optimization (ACO) is new meta heuristics method to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was firstly proposed for tackling the well known Traveling Salesman Problem (TSP) . In this paper, we introduce Multi Colony Ant Model that achieve positive interaction and negative interaction through Intensification and Diversification to improve original ACS performance. This algorithm is a method to solve problem through interaction between ACS groups that consist of some agent colonies to solve TSP problem. In this paper, we apply this proposed method to TSP problem and evaluates previous method and comparison for the performance and we wish to certify that qualitative level of problem solution is excellent.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37B no.12
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• pp.1102-1112
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• 2012

We propose a cell selection and resource allocation scheme that assigns users to nearby accessible cells in heterogeneous wireless networks consisting of macrocell, femtocells, and Wi-Fi access points, under overload situation. Given the current power level of all accessible cells nearby users, the proposed scheme finds all possible cell assignment mappings of which user should connect to which cell to maximize the number of users that the network can accommodate at the same time. We formulate the cell selection problem with heterogeneous cells into an optimization problem of binary integer programming, and compute the optimal solution. We evaluate the proposed algorithm in terms of network access failure compared to a local ad-hoc based cell selection scheme used in practical systems using network level simulations. We demonstrate that our cell selection algorithm dramatically reduces network access failure in overload situation by fully leveraging network resources evenly across heterogeneous networks. We also validate the practical feasibility in terms of computational complexity of our binary integer program by measuring the computation time with respect to the number of users.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.3
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• pp.155-160
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• 2017

Recently, Deep learning has been used successfully to solve many recognition problems. It has many advantages over existing machine learning methods that extract feature points through hand-crafting. Deep neural networks for human activity recognition split video data into frame images, and then classify activities by analysing the connectivity of frame images according to the time. But it is difficult to apply to actual problems which has small-scale activity classes. Because this situations has a problem of overfitting and insufficient training data. In this paper, we defined 5 type of small-scale human activities, and classified them. We construct video database using 700 video clips, and obtained a classifying accuracy of 74.00%.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.215-218
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• 2002

본 논문에서는 타원형 클러스터링을 위한 거리측정 함수로써 변형된 가무시안 커널 함수를 사용하며, 주어진 클러스터링 문제를 각 타원형 클러스터의 체적을 최소화하는 문제로 해석하고 이를 선형행렬 부등식 기법 중 하나인 고유값 문제로 변환하여 최적화하는 새로운 알고리즘을 제안한다.

• Korean Management Science Review
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• v.3
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• pp.58-61
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• 1986

본 고는 P사의 원료 수급에 관한 계량적 모델을 제시함으로써 문제의 규모와 복잡성 때문에 해결이 어려웠던 문제를 단계적 의사결정에 의해 접근함으로써 현상의 이해와 더불어 실제 응용을 가능케하기 위한 시도의 일환이다. 먼저 고려되어야 할 적정 재고수준의 산정과 배선계획은 향후 기술하기로 하며 컴퓨터의 발전과 더불어 조직적인 문제해결을 위한 계량적 모델을 통한 접근방법의 한 예를 기술하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.9 no.1
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• pp.33-40
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• 1989

In the design of reinforced concrete framed structures, which consist of various design variables, the objective and the constraint functions are formulated in complicated forms. Usually iterative methods have been used to optimize the design variables. In this paper, multilevel formulation is adopted, and design variables are selected in reduced numbers at each level, to reduce the iterative cycle and to accelerate the convergence rate. At level 1, elastic analysis is performed to get the upper and lower bounds of the redistributed design moments due to inelastic behavior of the frame. Then the design moments are taken as design variables and optimized at level 2, and the sizing variables are optimized at level 3. The optimization of redistributed moments is performed using the design sensitivity obtained at the level 2, and force approximation technique is used to reflect the variation of design variables in the lower level to the upper level. The design variables are selected in reduced numbers at each level, and the optimization formulation is simplified effectively. A cost function is taken as the objective function, and the constraints of the stress of the structures are derived from BSI CP 110 following limit state theory. Numerical examples are included to prove the effectiveness of the developed algorithm.

• Aerospace Engineering and Technology
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• v.12 no.2
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• pp.24-29
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• 2013

A spacecraft radiator is a thermal control method to eject internally dissipated heat into the space generated from operation of unit boxes. The efficiency of thermal design may be improved by optimizing radiator design. In this paper, the optimization approach method of node-based radiator design was suggested which is to combine numerical thermal analysis with optimization algorithm. This method has meaning that it can be used practically to implement the spacecraft radiator design regardless of thermal analysis and optimization algorithm software and maintain the same basic concept of an ordinary radiator design approach based on node division of a thermal model. The overall analysis framework with thermal analysis and optimization algorithm would be presented.