• 제목/요약/키워드: combinatorial approach

검색결과 116건 처리시간 0.028초

견실한 전력계통 상태벡터 계산을 위한 동기 페이저 측정기 최적배치 (Optimal Placement of Synchronized Phasor Measurement Units for the Robust Calculation of Power System State Vectors)

  • 조기선;신중린
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 A
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    • pp.75-79
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    • 2000
  • This paper proposes the optimal placement with minimum set of Phasor Measurement Units (PMU's) using tabu search and makes an alternative plan to secure the robustness of the network with PMU's. The optimal PMU Placement (OPP) problem is generally expressed as a combinatorial optimization problem subjected to the observability constraints. Thus, it is necessary to make a use of an efficient method in solving the OPP problem. In this paper, a tabu search based approach to solve efficiently this OPP problem proposed. The observability of the network with PMU's is fragile at any single PMU contingency. To overcome the fragility, an alternative scheme that makes efficient use of the existing measurement system in power system state estimation proposed. The performance of the proposed approach and the alternative scheme is evaluated with IEEE sample systems.

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경쟁 공진화알고리듬을 이용한 다목적 Job shop 일정계획 (Multi-objective job shop scheduling using a competitive coevolutionary algorithm)

  • 이현수;신경석;김여근
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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    • pp.1071-1076
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    • 2003
  • Evolutionary algorithm is recognized as a promising approach to solving multi-objective combinatorial optimization problems. When no preference information of decision makers is given, multi-objective optimization problems have been commonly used to search for diverse and good Pareto optimal solution. In this paper we propose a new multi-objective evolutionary algorithm based on competitive coevolutionary algorithm, and demonstrate the applicability of the algorithm. The proposed algorithm is designed to promote both population diversity and rapidity of convergence. To achieve this, the strategies of fitness evaluation and the operation of the Pareto set are developed. The algorithm is applied to job shop scheduling problems (JSPs). The JSPs have two objectives: minimizing makespan and minimizing earliness or tardiness. The proposed algorithm is compared with existing evolutionary algorithms in terms of solution quality and diversity. The experimental results reveal the effectiveness of our approach.

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A Route-Splitting Approach to the Vehicle Routing Problem

  • 강성민
    • 한국경영과학회:학술대회논문집
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    • 한국경영과학회 2004년도 추계학술대회 및 정기총회
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    • pp.389-392
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    • 2004
  • The column generation process for the set-partitioning model of the vehicle routing problem requires repeated solutions of column generation subproblems which has a combinatorial structure similar to that of the traveling salesman problem. This limits the size of the problem that can be addressed. We introduce a new modeling approach, termed route-splitting, which splits each vehicle route into segments, and results in more tractable subproblems. A lower bounding scheme that yields an updated bound at each iteration of the column generation process is developed. Implementation issues, including a technique of controlling columns in the master problem, are explored. Lower bounds are computed on standard benchmark problems with up to 199 customers.

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분권화된 다중 프로젝트 관리를 위한 시장 기반 모델링 (Market-based Modeling of Decentralized Multiple Project Management)

  • 이용한
    • 한국IT서비스학회:학술대회논문집
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    • 한국IT서비스학회 2003년도 춘계학술대회
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    • pp.577-583
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    • 2003
  • Due to the widespread availability of the internet, large-scale and dynamic distributed projects in industry are becoming popular. We present a distributed, collaborative, and adaptive control approach for decentralized multiple projects, which is one of representative project environments in modern e-enterprises. In this paper we deal with short term scheduling and rescheduling of resources, which are shared by multiple projects. We in specific, address the dynamic nature of the situation. We model this as a dynamic economy, where the multiple local markets are established and cleared over time trading resource time slots(goods). Local markets are modeled using a combinatorial auction mechanism. Due to the dynamic and distributed nature of economy, through our approach we can achieve higher levels of flexibility, scalability and adaptability.

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A Genetic Algorithm Approach for the Design of Minimum Cost Survivable Networks with Bounded Rings

  • B. Ombuki;M. Nakamura;Na, Z.kao;K.Onage
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 ITC-CSCC -1
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    • pp.493-496
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    • 2000
  • We study the problem of designing at minimum cost a two-connected network topology such that the shortest cycle to which each edge belongs does not exceed a given maximum number of hops. This problem is considered as part of network planning and arises in the design of backbone networks. We propose a genetic algorithm approach that uses a solution representation, in which the connectivity and ring constraints can be easily encoded. We also propose a crossover operator that ensures a generated solution is feasible. By doing so, the checking of constraints is avoided and no repair mechanism is required. We carry out experimental evaluations to investigate the solution representation issues and GA operators for the network design problem.

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유전자알고리즘을 적용한 위성고객할당 최적 설계 (Optimal Design of Satellite Customer Assignment using Genetic Algorithm)

  • 김성수;김중현;김기동;이선엽
    • 산업공학
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    • 제19권4호
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    • pp.300-305
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    • 2006
  • The problem of assigning customers to satellite channels is considered in this paper. Finding an optimal allocation of customers to satellite channels is a difficult combinatorial optimization problem and is shown to be NP-complete in an earlier study. We propose a genetic algorithm (GA) approach to search for the best/optimal assignment of customers to satellite channels. Various issues related to genetic algorithms such as solution representation, selection methods, genetic operators and repair of invalid solutions are presented. A comparison of GA with CPLEX8.1 is presented to show the advantages of this approach in terms of computation time and solution quality.

Bounded QEA 기반의 발전기 기동정지계획 연구 (A Thermal Unit Commitment Approach based on a Bounded Quantum Evolutionary Algorithm)

  • 장세환;정윤원;김욱;박종배;신중린
    • 전기학회논문지
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    • 제58권6호
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    • pp.1057-1064
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    • 2009
  • This paper introduces a new approach based on a quantum-inspired evolutionary algorithm (QEA) to solve unit commitment (UC) problems. The UC problem is a complicated nonlinear and mixed-integer combinatorial optimization problem with heavy constraints. This paper proposes a bounded quantum evolutionary algorithm (BQEA) to effectively solve the UC problems. The proposed BQEA adopts both the bounded rotation gate, which is simplified and improved to prevent premature convergence and increase the global search ability, and the increasing rotation angle approach to improve the search performance of the conventional QEA. Furthermore, it includes heuristic-based constraint treatment techniques to deal with the minimum up/down time and spinning reserve constraints in the UC problems. Since the excessive spinning reserve can incur high operation costs, the unit de-commitment strategy is also introduced to improve the solution quality. To demonstrate the performance of the proposed BQEA, it is applied to the large-scale power systems of up to 100-unit with 24-hour demand.

혈장 시료 풀링을 통한 신약 후보물질의 흡수율 고효율 검색기법의 평가 (Evaluation of a Sample-Pooling Technique in Estimating Bioavailability of a Compound for High-Throughput Lead Optimazation)

  • 이인경;구효정;정석재;이민화;심창구
    • Journal of Pharmaceutical Investigation
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    • 제30권3호
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    • pp.191-199
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    • 2000
  • Genomics is providing targets faster than we can validate them and combinatorial chemistry is providing new chemical entities faster than we can screen them. Historically, the drug discovery cascade has been established as a sequential process initiated with a potency screening against a selected biological target. In this sequential process, pharmacokinetics was often regarded as a low-throughput activity. Typically, limited pharmacokinetics studies would be conducted prior to acceptance of a compound for safety evaluation and, as a result, compounds often failed to reach a clinical testing due to unfavorable pharmacokinetic characteristics. A new paradigm in drug discovery has emerged in which the entire sample collection is rapidly screened using robotized high-throughput assays at the outset of the program. Higher-throughput pharmacokinetics (HTPK) is being achieved through introduction of new techniques, including automation for sample preparation and new experimental approaches. A number of in vitro and in vivo methods are being developed for the HTPK. In vitro studies, in which many cell lines are used to screen absorption and metabolism, are generally faster than in vivo screening, and, in this sense, in vitro screening is often considered as a real HTPK. Despite the elegance of the in vitro models, however, in vivo screenings are always essential for the final confirmation. Among these in vivo methods, cassette dosing technique, is believed the methods that is applicable in the screening of pharmacokinetics of many compounds at a time. The widespread use of liquid chromatography (LC) interfaced to mass spectrometry (MS) or tandem mass spectrometry (MS/MS) allowed the feasibility of the cassette dosing technique. Another approach to increase the throughput of in vivo screening of pharmacokinetics is to reduce the number of sample analysis. Two common approaches are used for this purpose. First, samples from identical study designs but that contain different drug candidate can be pooled to produce single set of samples, thus, reducing sample to be analyzed. Second, for a single test compound, serial plasma samples can be pooled to produce a single composite sample for analysis. In this review, we validated the issue whether the second method can be applied to practical screening of in vivo pharmacokinetics using data from seven of our previous bioequivalence studies. For a given drug, equally spaced serial plasma samples were pooled to achieve a 'Pooled Concentration' for the drug. An area under the plasma drug concentration-time curve (AUC) was then calculated theoretically using the pooled concentration and the predicted AUC value was statistically compared with the traditionally calculated AUC value. The comparison revealed that the sample pooling method generated reasonably accurate AUC values when compared with those obtained by the traditional approach. It is especially noteworthy that the accuracy was obtained by the analysis of only one sample instead of analyses of a number of samples that necessitates a significant man-power and time. Thus, we propose the sample pooling method as an alternative to in vivo pharmacokinetic approach in the selection potential lead(s) from combinatorial libraries.

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생물지리학적 최적화를 적용한 이동체 리포팅 셀 시스템 설계 (Biogeography Based Optimization for Mobile Station Reporting Cell System Design)

  • 김성수
    • 산업경영시스템학회지
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    • 제43권1호
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    • pp.1-6
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    • 2020
  • Fast service access involves keeping track of the location of mobile users, while they are moving around the mobile network for a satisfactory level of QoS (Quality of Service) in a cost-effective manner. The location databases are used to keep track of Mobile Terminals (MT) so that incoming calls can be directed to requested mobile terminals at all times. MT reporting cell system used in location management is to designate each cell in the network as a reporting cell or a non-reporting cell. Determination of an optimal number of reporting cells (or reporting cell configuration) for a given network is reporting cell planning (RCP) problem. This is a difficult combinatorial optimization problem which has an exponential complexity. We can see that a cell in a network is either a reporting cell or a non-reporting cell. Hence, for a given network with N cells, the number of possible solutions is 2N. We propose a biogeography based optimization (BBO) for design of mobile station location management system in wireless communication network. The number and locations of reporting cells should be determined to balance the registration for location update and paging operations for search the mobile stations to minimize the cost of system. Experimental results show that our proposed BBO is a fairly effective and competitive approach with respect to solution quality for optimally designing location management system because BBO is suitable for combinatorial optimization and multi-functional problems.

센서 네트워크 구축에서의 Combinatorial 기법 적용 (The application of the combinatorial schemes for the layout design of Sensor Networks)

  • 김준모
    • 대한전자공학회논문지TC
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    • 제45권7호
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    • pp.9-16
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    • 2008
  • 센서 네트워크에서의 효율적인 라우팅을 위하여 센서노드들을 최적으로 상호연결 하는 배치를 찾는 문제를 고려하게 된다. 유사한 이론 문제로서 평면상에 주어진 점들을 최적으로 상호연결 하는 트리 구조를 찾는 스타이너 트리 문제가 있는데, 이 문제에 대한 근사 알고리즘을 차용하여 센서노드들을 최적에 근사하게 상호연결 하는 배치를 찾을 수도 있다. 하지만 스타이너 트리 문제는 평면상에서 수학적으로 정의된 점들의 집합을 상호연결 하는 문제로서 센서 네트워크에서는 나타나지 않는 특수한 경우까지 내포하므로, 그 알고리즘을 사용하는 접근은 타당한 분석 방식이 될 수 없다. 센서 네트워크에서 센서들의 분포는 평면상의 수학적인 점들의 임의적인 분포와는 달리, 센서들이 일정거리 이상으로 서로 떨어져 있다고 가정 할 수 있다. 이러한 물리적인 성격을 반영하여 센서 네트워크를 위한 근사 알고리즘을 구성함으로써, 센서 네트워크 상호연결이라는 문제에 적합한 실행시간 및 최적치에 대한 근사비율을 도출 할 수 있게 된다.