• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.84-92
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• 2007

Dynamic process planning requires not only more flexible capabilities of a CAPP system but also higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations by calculating the machine loads. The developed algorithm is based on the multi-objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as the Pareto-optimal solutions). The objective is to satisfy both the minimization number of part movements and the maximization of machine utilization. The algorithm is characterized by a new and efficient method for nondominated sorting through K-means algorithm, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II and branch and bound algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.91-100
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• 1990

This paper is concerned with the development of optimal algorithms for multi-stage flowshop scheduling problems with sequence dependent setup times. In the previous researches the setup time of a job is considered to be able to begin at the earliest opportunity given a particular sequence at the start of operations. In this paper the setup time of a job is considered to be able to begin only at the completion of that job on the previous machine to reflect the effects of the setup time to the performance measure of sequence dependent setup time flowshop scheduling. The results of the study consist of two areas; first, a general integer programming(IP) model is formulated and a nixed integer linear programming(MILP) model is also formulated by introducing a new binary variable. Second a depth-first branch and bound algorithm is developed. To reduce the computational burdens we use the best heuristic schedule developed by Choi(1989) as the first trial. The experiments for developed algorithm are designed for a 4$\times$3$\times$3 factorial design with 360 observations. The experimental factors are PS(ratio of processing time to setup time), M(number of machines), N(number of jobs).

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.261-265
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• 2004

This paper proposes a fuzzy dual method for analyzing long-term transmission system expansion planning problem considering ambiguities of the power system using fuzzy lineal programming. Transmission expansion planning problem can be formulated integer programming or linear programming with minimization total cost subject to reliability (load balance). A long-term expansion planning problem of a grid is very complex, which have uncertainties fur budget, reliability criteria and construction time. Too much computation time is asked for actual system. Fuzzy set theory can be used efficiently in order to consider ambiguity of the investment budget (economics) for constructing the new transmission lines and the delivery marginal rate (reliability criteria) of the system in this paper. This paper presents formulation of fuzzy dual method as first step for developing a fuzzy Ford-Fulkerson algorithm in future and demonstrates sample study. In application study, firstly, a case study using fuzzy integer programming with branch and bound method is presented for practical system. Secondly, the other case study with crisp Ford Fulkerson is presented.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06b
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• pp.298-302
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• 2008

주어진 작은 크기의 칩 내부에 많은 기능 (예: 멀티미디어, 음성/영상 등)을 작동시키기 위해서는 고집적(high-integration)의 회로가 구현되게 된다. 이러한 고집적 회로는 작동할 때 상당한 양의 전력 소모를 유발하게 되어 결국 배더리 수명을 단축시키는 상황을 가지게 한다. 더욱 심각한 상황은 고 밀도의 칩 안에서의 많은 전력 소모는 열의 발생을 더욱 가속화 시키게 되며, 결국 칩 작동의 신뢰성(reliability)을 상당히 잃게 만든다. 본 연구에서는 칩의 작동에 따른 열 발생으로 유발되는 칩의 온도 상승을 감지하는 센서회로 구현에 관한 것이다. FPGA 칩은 주 목적의 기능을 수행하는 회로들을 구현함과 동시에 추가적으로 열 감지 센서 회로를 구현할 자원을 FPGA가 제공을 해 주어야 하는데, 주목적의 회로 공간(즉, 자원) 사용으로 인해 열 센서 회로 구현 자원이 충분하지 않을 경우나 여러 지역에 사용 가능한 자원이 소규모로 흩어진 경우 등 센서 구현을 위한 자원 탐색 및 구현 가능성에 대해 점검하는 알고리즘이 필요하다. 본 연구는 이러한 알고리즘을 개발하여 그 효용성을 실험을 통해 보이고 있다. 제안한 알고리즘의 특징은 Branch-and-Bound에 기반을 두고 있으며, 알고리즘의 수행 시간 단축을 위한 효과적인 search tree pruning 기법을 제안하고 있다.

• Journal of the Korea Computer Industry Society
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• v.5 no.3
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• pp.377-382
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• 2004

An unconstrained three-dimensional cutting problem describes the process of finding the cutting pattern that yields the maximum total profit-sum for the small parallelepipeds pieces cut from a large parallelepiped box and there is no limit to the number of pieces to be cut. The problem is a classic NP-hard. The bottom-up approach, which generates all of the feasible cutting patterns by combining two other cutting patterns, can be applied to the three-dimensional problem. We introduce a build and new branching strategies for the unconstrained three-dimensional cutting problem. The strategies are all generalized from the branching strategies proposed by G et at. to solve unconstrained two-dimensional cutting problems.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.297-300
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• 2004

This paper proposes a method for choosing the best composite power system expansion plan considering probabilistic reliability criterion. The proposed method was modeled as the minimization of the investment budget (economics) for constructing new transmission lines subject to not only deterministic(demand constraint) but also probabilistic reliability criterion(LOLE) with considering the uncertainties of the system elements. This is achieved by modeling the power system expansion problem as an integer programming one. The method solves for the optimal strategy using a probabilistic theory based branch and bound method that utilizes a network flow approach and the maximum flow-minimum cut set theorem. Although the proposed method is applied to a simple sample study, the test results demonstrate a fact that the proposed method is suitable for solving the power system expansion planning problem subject to practical uncertainties for future.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.574-575
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• 2007

This paper proposes a method for choosing the best transmission system expansion plan using nodal/bus delivery marginal rate criterion ($BMR_k$) defined newly in this paper. The objective method minimizes a total cost which is an investment budget for constructing new transmission lines subject to the $BMR_k$ which means a nodal deterministic reliability level requirement at specified load point. The proposed method models the transmission system expansion problem as an integer programming problem. It solves for the optimal strategy using a branch and bound method that utilizes a network flow approach and the maximum flow-minimum cut set theorem. Test results on an existing 21-bus system are included in the paper. It demonstrated the suitability of the proposed method for solving the transmission system expansion planning problem in competitive electricity market environment.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.501-502
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• 2015

매년 증가되는 전력소비량에 대응하여 스마트그리드 기술을 기반으로 수용가 측의 에너지관리 중요성이 부각되고 있으며, 홈 에너지관리시스템(HEMS, Home Energy Management System)은 전기요금 절감과 효율적인 전력소비의 중요한 체계로써 기대되고 있다. 일반적으로, 가정에서 높은 전력소비를 가진 가전제품은 계절성 부하로 전기온수기, 냉/난방기를 일컫는다. 즉, 계절성 부하에 적절한 에너지관리, '최적부하 스케줄링'은 전기요금 절감과 직결되는 것을 의미한다. 본 논문은 Modified Branch-and-Bound 기법을 사용하여 사용자의 편의성을 고려한 전기온수기(EWH, Electric Water Heater)의 스케줄링을 실시하겠다. 여기서 사용자의 편의성이란, 외부의 온도변화 또는 습관에 따라 그 부하를 사용하는 것을 의미한다. 온수사용량, 수온 설정온도 변화의 편의성 제약조건을 고려하여 온수기를 효과적으로 운영하는 스케줄링을 실시한다. 이러한 편의성 내에서 온수기를 운영하며, 작동모드는 3가지(정지, 일반/급속가열) 모드가 존재하며, 다양한 요금제도에서의 스케줄링 결과를 절감된 전기요금으로 비교하겠다.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.6
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• pp.755-760
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• 2010

In general, Lagrangian method for discrete optimization is a kind of technique to easily manage constraints. It is traditionally used for finding upper bounds in the branch-and-bound method. In this paper, we propose a new Lagrangian search method for the 0-1 knapsack problem with multiple constraints. A novel feature of the proposed method different from existing Lagrangian approaches is that it can find high-quality lower bounds, i.e., feasible solutions, efficiently based on a new property of Lagrangian vector. We show the performance improvement of the proposed Lagrangian method over existing ones through experiments on well-known large scale benchmark data.

• ETRI Journal
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• v.5 no.3
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• pp.3-8
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• 1983

In the area of computer network planning, a location-allocation-size problem is involved. Since multi-facility location-allocation-size problems are very complex in formulating a mathematical model, it is a usual practise to adopt alternative approaches, which give no optimal results, instead of the optimal solution by mathematical approach. In this article, however, an attempt is made to formulate a mathematical model for the decision making problem of computer network design.