• 제목/요약/키워드: Constraint programming

검색결과 262건 처리시간 0.021초

Redundancy Optimization for the Mixed Reliability System

  • Sok, Yong-U
    • 한국국방경영분석학회지
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    • 제26권2호
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    • pp.143-158
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    • 2000
  • This paper deals with the problem of redundancy allocation for the mixed reliability system in an optimal way. Two kinds of the reliability system are considered for optimal allocation of parallel redundancy. The problem is approached as the optimization problems using th standard method of dynamic programming(DP). The algorithm for solving the optimal redundancy allocation is proposed and then the DP algorithm is applied to two numerical examples such as maximization of reliability subject to an allowable cost-constraint and minimization of the total cost subject to the specified minimum reliability-constraint. A consequence of this study is that the developed computer program package can be applied to the optimal redundancy allocation for the mixed reliability system.

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MPLS 기반 IP 방에서 열생성 기법을 이용한 경로 설정 해법 (Column Generation Approach to the Constraint Based Explicit Routing Problem in MPLS Based IP Networks)

  • 김덕성;박성수
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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    • pp.410-417
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    • 2002
  • We consider the constraint based explicit routing problem in MPLS based IP Network. In this problem, we are given a set of traffic demands and a network with different link capacities. The problem is to assign the demand commodities to the paths in the network while minimizing the maximum link load ratio. We formulate this problem as an integer programming problem and propose an efficient column generation technique. To strengthen the formulation, we consider some valid inequalities. We also incorporate the column generation technique with variable fixing scheme Computational results show that the algorithm gives high quality solutions in a short execution time.

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제약조건이 있는 시뮬레이션을 위한 계층적 모델링 방법론 (Hierarchical Modeling Methodology for Contraint Simulations)

  • 이강선
    • 한국시뮬레이션학회논문지
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    • 제9권4호
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    • pp.41-50
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    • 2000
  • We have many simulation constraints to meet as a modeled system becomes large and complex. Real-time simulations are the examples in that they are constrained by certain non-function constraints (e.g., timing constraints). In this paper, an enhanced hierarchical modeling methodology is proposed to efficiently deal with constraint-simulations. The proposed modeling method enhances hierarchical modeling methods to provide multi-resolution model. A simulation model is composed by determining the optimal level of abstraction that is guaranteed to meet the given simulation constraints. Four modeling activities are defined in the proposed method: 1) Perform the logical architectural design activity to produce a multi-resolution model, 2) Organize abstraction information of the multi-resolution model with AT (Abstraction Tree) structure, 3) Formulate the given constraints based on U (Integer Programming) approach and embrace the constraints to AT, and 4) Compose a model based on the determined level of abstraction with which the multi-resolution model can satisfy all given simulation constraints. By systematically handling simulation constraints while minimizing the modeler's interventions, we provide an efficient modeling environment for constraint-simulations.

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A New Ship Scheduling Set Packing Model Considering Limited Risk

  • Kim, Si-Hwa;Hwang, Hee-Su
    • 한국항해항만학회지
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    • 제30권7호
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    • pp.561-566
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    • 2006
  • In this paper, we propose a new ship scheduling set packing model considering limited risk or variance. The set packing model is used in many applications, such as vehicle routing, crew scheduling, ship scheduling, cutting stock and so on. As long as the ship scheduling is concerned, there exits many unknown external factors such as machine breakdown, climate change and transportation cost fluctuation. However, existing ship scheduling models have not considered those factors apparently. We use a quadratic set packing model to limit the variance of expected cost of ship scheduling problems under stochastic spot rates. Set problems are NP-complete, and additional quadratic constraint makes the problems much harder. We implement Kelley's cutting plane method to replace the hard quadratic constraint by many linear constrains and use branch-and-bound algorithm to get the optimal integral solution. Some meaningful computational results and comments are provided.

GENETIC ALGORITHMIC APPROACH TO FIND THE MAXIMUM WEIGHT INDEPENDENT SET OF A GRAPH

  • Abu Nayeem, Sk. Md.;Pal, Madhumangal
    • Journal of applied mathematics & informatics
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    • 제25권1_2호
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    • pp.217-229
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    • 2007
  • In this paper, Genetic Algorithm (GA) is used to find the Maximum Weight Independent Set (MWIS) of a graph. First, MWIS problem is formulated as a 0-1 integer programming optimization problem with linear objective function and a single quadratic constraint. Then GA is implemented with the help of this formulation. Since GA is a heuristic search method, exact solution is not reached in every run. Though the suboptimal solution obtained is very near to the exact one. Computational result comprising an average performance is also presented here.

최적 생산/판매 계획을 통한 기업 목표 관리 사례 (Management for Company Objectives with Considerations of Optimal Production/Sales Planning)

  • 정재헌
    • 한국경영과학회지
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    • 제34권2호
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    • pp.77-90
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    • 2009
  • Total profit level Increases if a company increase the cost for achieving R&D related goals of equipment productivity enhancement, production cost saving, or for achieving equipment scale target, sales volume goal. But how much money should be invested to achieve a certain level of profit? We formulated the model to set the optimal goal levels to minimize the investment cost under the constraint that certain level of total profit should be guaranteed. This model derived from a case of P steel company. We found that this should be considered in relation with the production sales planning (known as optimal product mix problem) to guarantee the profit. We suggested a nonlinear programming model, 3 valiant form of the p+roduct mix problem. We can find the optimal Investment level for the R&D related goals or sales volume goal, equipment scale target for the P steel company using the model.

복소형 다각형 불변영역을 이용한 입력제한 예측제어 (Input Constrained Receding Horizon Control Using Complex Polyhedral Invariant Region)

  • 이영일;방대인;윤태웅;김기용
    • 제어로봇시스템학회논문지
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    • 제8권12호
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    • pp.991-997
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    • 2002
  • The concept of feasible & invariant region plays an important role to derive closed loop stability and achie adequate performance of constrained receding horizon predictive control. In this paper, we define a complex polyhedral feasible & invariant set for all stabilizable input-constrained linear systems by using a complex transform and propose a one-norm based receding horizon control scheme using these invariant sets. In order to get a larger stabilizable set, a convex hull of invariant sets which are defined for different state feedback gains is used as a target invariant set of the constrained receding horizon control. The proposed constrained receding horizon control scheme is formulated so that it can be solved via linear programming.

AN OPTIMAL BOOSTING ALGORITHM BASED ON NONLINEAR CONJUGATE GRADIENT METHOD

  • CHOI, JOOYEON;JEONG, BORA;PARK, YESOM;SEO, JIWON;MIN, CHOHONG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제22권1호
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    • pp.1-13
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    • 2018
  • Boosting, one of the most successful algorithms for supervised learning, searches the most accurate weighted sum of weak classifiers. The search corresponds to a convex programming with non-negativity and affine constraint. In this article, we propose a novel Conjugate Gradient algorithm with the Modified Polak-Ribiera-Polyak conjugate direction. The convergence of the algorithm is proved and we report its successful applications to boosting.

Document Summarization via Convex-Concave Programming

  • Kim, Minyoung
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권4호
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    • pp.293-298
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    • 2016
  • Document summarization is an important task in various areas where the goal is to select a few the most descriptive sentences from a given document as a succinct summary. Even without training data of human labeled summaries, there has been several interesting existing work in the literature that yields reasonable performance. In this paper, within the same unsupervised learning setup, we propose a more principled learning framework for the document summarization task. Specifically we formulate an optimization problem that expresses the requirements of both faithful preservation of the document contents and the summary length constraint. We circumvent the difficult integer programming originating from binary sentence selection via continuous relaxation and the low entropy penalization. We also suggest an efficient convex-concave optimization solver algorithm that guarantees to improve the original objective at every iteration. For several document datasets, we demonstrate that the proposed learning algorithm significantly outperforms the existing approaches.

MOEPE: 스테레오 정합 하드웨어를 위한 Merged Odd-Even PE 구조 (MOEPE: Merged Odd-Even PE Architecture for Stereo Matching Hardware)

  • 한필우;양영일
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 1998년도 추계종합학술대회 논문집
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    • pp.1137-1140
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    • 1998
  • In this paper, we propose the new hardware architecture which implements the stereo matching algorithm using the dynamic programming method. The dynamic programming method is used in finding the corresponding pixels between the left image and the right image. The proposed MOEPE(Merged Odd-Even PE) architecture operates in the systolic manner and finds the disparities from the intensities of the pixels on the epipolar line. The number of PEs used in the MOEPE architecture is the number of the range constraint, which reduced the number of the necessary PEs dramatically compared to the traditional method which uses the PEs with the number of pixels on the epipolar line. For the normal method by 25 times. The proposed architecture is modeled with the VHDL code and simulated by the SYNOPSYS tool.

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