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MR&MR-SUM: MAXIMUM RELEVANCE AND MINIMUM REDUNDANCY DOCUMENT SUMMARIZATION MODEL

INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2013年第3期12卷 361-393页

作者： Alguliev, Rasim M. Aliguliyev, Ramiz M. Isazade, Nijat R. Azerbaijan Natl Acad Sci Inst Informat Technol AZ-1141 Baku Azerbaijan

We have presented an approach to automatic document summarization. In the proposed approach, text summarization is modeled as a quadratic integer-programming problem. This model generally attempts to optimize three properties, namely, (1) relevance: summary should contain informative textual units that are relevant to the user;(2) redundancy: summaries should not contain multiple textual units that convey the same information;and (3) length: summary is bounded in length. To solve the optimization problem we have created a novel differential evolution algorithm. Experimental results on DUC2005 and DUC2007 data sets showed that the proposed approach outperforms the other methods. Doubt in Title

关键词： Unsupervised document summarization maximum relevance minimum redundancy quadratic integer programming differential evolution algorithm combined similarity measure

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Evaluating the quality of image matrices in blockmodeling

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EURO JOURNAL ON COMPUTATIONAL OPTIMIZATION 2015年第2期3卷 111-129页

作者： Wiesberg, Stefan Reinelt, Gerhard Heidelberg Univ Inst Informat Neuenheimer Feld 368 D-69120 Heidelberg Germany

One approach for analyzing large networks is to partition its nodes into classes where the nodes in a class have similar characteristics with respect to their connections in the network. A class is represented as a blockmodel (or image matrix). In this context, a specific question is to test whether a presumed blockmodel is well reflected in the network or to select from a choice of possible blockmodels the one fitting best. In this paper, we formulate these problems as combinatorial optimization problems. We show that the evaluation of a blockmodel's quality is a generalization of well- known optimization problems such as quadratic assignment, minimum kcut, traveling salesman, and minimum edge cover. A quadratic integer programming formulation is derived and linearized by making use of properties of these special cases. With a branch- and- cut approach, the resulting formulation is solved up to 10,000 times faster than a comparable formulation from the literature.

关键词： Regular equivalence Blockmodeling quadratic integer programming Linearization techniques

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A quadratic integer-PROGRAM FOR THE LOCATION OF INTERACTING HUB FACILITIES

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1987年第3期32卷 393-404页

作者： O'KELLY, ME OHIO STATE UNIV DEPT GEOG 103 BRICKER HALL 190 N OVAL MALL COLUMBUS OH 43210 USA

This paper reports a new formulation of a general hub location model as a quadratic integer program. Non-convexity of the objective function makes the problem difficult. A variety of alternative solution strategies are discussed. Computational results from two simple heuristics are presented for the task of siting 2, 3 or 4 hubs to serve interactions between sets of 10, 15, 20 and 25 U.S. cities. The effects of different computational shortcuts are examined. [ABSTRACT FROM AUTHOR]

关键词： Location quadratic integer programming spatial interaction

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ON TABU SEARCH FOR THE LOCATION OF INTERACTING HUB FACILITIES

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1994年第3期73卷 502-509页

作者： SKORINKAPOV, D SKORINKAPOV, J SUNY STONY BROOK WA HARRIMAN SCH MANAGEMENT & POLICY STONY BROOK NY 11794 USA

A new heuristic method based on tabu search is developed for the problem of locating p interacting hub facilities among n interacting nodes in a network. The method treats equally the problem of locating hub facilities, as well as the problem of allocating the nodes to one and only one hub. The algorithm obtained improved solutions to problems from the standard test set from literature which has been used in this study.

关键词： LOCATION quadratic integer programming HEURISTICS TABU SEARCH

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An optimization tool for energy efficiency of street lighting systems in smart cities

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IFAC-PapersOnLine 2017年第1期50卷 14460-14464页

作者： Carli, Raffaele Dotoli, Mariagrazia Cianci, Edmondo Dept. of Electrical and Information Engineering Politecnico di Bari Bari Italy

This paper develops a decision making tool to support the public decision maker in selecting the optimal energy retrofit interventions on an existing street lighting system. The problem statement is based on a quadratic integer programming formulation and deals with simultaneously reducing the energy consumption and ensuring an optimal allocation of the retrofit actions among the street lighting subsystems. The methodology is applied to a real street lighting system in Bari, Italy. The obtained results demonstrate that the approach effectively supports the city governance in making decisions for the optimal energy management of the street lighting. © 2017

关键词： Decision making Energy efficiency Energy utilization integer programming Lighting fixtures Optimization Retrofitting Smart city Street lighting Decision making tool Distribution management systems Energy Optimal allocation Optimization tools Problem statement quadratic integer programming Street lighting system

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A New Model of Generalized Assignment Problem and Its Method 2

A New Model of Generalized Assignment Problem and Its Method

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2nd IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Xiong, Sheng Yang, Yuqi Huai, Kaizhan PLA Univ Sci & Technol Inst Commun Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781467389792

The traditional assignment problem assumes that the number of persons is equal to that of the tasks, beyond that, one person is allowed to undertake only one task and one task must be accomplished by one person. However, in practical situation, a real task usually calls for more than one person, in some cases, those persons are required to work at the same time. If so, the classical assignment model will not be able to describe the problem accurately. In view of this situation, a new generalized assignment model based on nonlinear integer programming is presented in this paper. The new model gives a unified description of the generalized assignment problems in which one or more persons are required to work at the same time to complete a single task. As a result, it makes up for the deficiency of the existing generalized assignment model. Moreover, for the case of binary quadratic programming, a new branch and bound method is also proposed. The numerical results indicate that the generalized assignment model and method proposed are valid.

关键词： Generalized assignment problem Nonlinear integer programming quadratic integer programming Branch and bound method

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ON A quadratic integer-PROGRAM FOR THE LOCATION OF INTERACTING HUB FACILITIES

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 1990年第3期46卷 409-411页

作者： AYKIN, T RUTGERS STATE UNIV NEWARKNJ 07102 USA

The article discusses a quadratic integer program for the location of interacting hub facilities and the node assignments that minimize the total transportation cost. M.E. O'Kelly has proposed two heuristics, called HEUR 1 and HEUR 2, involving a complete enumeration of the locational configurations, and proximity based assumptions about allocation. HEUR 1 involves a complete enumeration of the locational configurations and allocation of every non-hub node to its nearest hub. The objective function of the model developed by O'Kelly involves transportation costs rather than distances. Thus, an explicit assumption in O'Kelly's analysis is that the transportation cost is directly proportional to the distance. The nearest hub assignment is then the same with the least unit transportation cost assignment. Note that this allocation rule may assign a node to different hub facilities if the transportation cost is not directly proportional to the distance. In this case, the nearest hub rule may be totally inappropriate.

关键词： Location quadratic integer programming spatial interaction

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Matching misaligned two-resolution metrology data

Matching misaligned two-resolution metrology data

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作者： Wang, Yaping Texas A&M University

学位级别：Ph.D.

Multi-resolution metrology devices co-exist in today's manufacturing environment, producing coordinate measurements complementing each other. Typically, the high-resolution device produces a scarce but accurate dataset, whereas the low-resolution one produces a dense but less accurate dataset. Research has shown that combining the two datasets of different resolutions makes better predictions of the geometric features of a manufactured part. A challenge, however, is how to effectively match each high-resolution data point to a low-resolution point that measures approximately the same physical location. A solution to this matching problem appears a prerequisite to a good final prediction. This dissertation solves this metrology matching problem by formulating it as a quadratic integer programming, aiming at minimizing the maximum inter-point-distance difference (maxIPDdiff) among all potential correspondences. Due to the combinatorial nature of the optimization model, solving it to optimality is computationally prohibitive even for a small problem size. In order to solve real-life sized problems within a reasonable amount of time, a two-stage matching framework (TSMF) is proposed. The TSMF approach follows a coarse-to-fine search strategy and consists of down-sampling the full size problem, solving the down-sampled problem to optimality, extending the solution of the down-sampled problem to the full size problem, and refining the solution using iterative local search. Many manufactured parts are designed with symmetric features; that is, many part surfaces are invariant (are mapped to themselves) to certain intrinsic reflections and/or rotations. Dealing with parts surfaces with symmetric features makes the metrology matching problem even more challenging. The new challenge is that, due to this symmetry, alignment performance metrics such as maxIPDdiff and root mean square error are not able to differentiate between (a) correct solutions/correspondences that are orie

关键词： Coordinate measuring machine correspondences iterative closest point (ICP) coherent point drift (CPD) two-stage matching framework quadratic integer programming rigid point set registration Thesis

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Index Tracking com controle do número de ativos e aplicação com uso de algoritmos genéticos

Index Tracking com controle do número de ativos e aplicaç...

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作者： Sant’anna, Leonardo Riegel

In this master’s thesis it is discussed the portfolio optimization problem using the passive investment strategy of Index Tracking. The main goals are (i) to present an optimization model for the Index Tracking problem and (ii) to solve this model using the heuristic approach of Genetic Algorithms (GA) to create portfolios with reduced amount of stocks. The benchmark used is the Ibovespa Index (main reference for the Brazilian Stock Market), during the period from January/2009 to July/2012 (using a total of 890 daily stock prices). The sample contains 67 assets, and the model is used to build portfolios without limit in the amount of assets and portfolios limited to 40, 30, 20, 10 and 05 assets; the ranges of time to rebalance the portfolios are 20, 40, and 60 trading days, which means to rebalance monthly, bimonthly and quarterly. The results show that, considering this sample, it is not possible to build portfolios with 20 stocks (or less than 20) through direct optimization using the solver Cplex with computational processing time less than 1 hour and results with gap below 5%. On the other hand, using the Genetic Algorithms heuristic approach, portfolios limited to 10 and 05 stocks are built with computational time close to 5 minutes; for both types of portfolio, the solutions provided by the GA have average gap below 10%. Also, with a computational time slightly bigger, close to 8 minutes, the algorithm provides solutions with average gap below 5% for portfolios limited to 10 and 05 stocks. ...

关键词： Index track Carteiras de investimento Otimização Portfolio optimization quadratic integer programming Algoritmo genético Asset management Dissertação

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A result on the Slope conjectures for 3-string Montesinos knots

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JOURNAL OF KNOT THEORY AND ITS RAMIFICATIONS 2018年第13期27卷

作者： Leng, Xudong Yang, Zhiqing Liu, Ximin Dalian Univ Technol Sch Math Sci Dalian 116024 Peoples R China

The Slope Conjecture and the Strong Slope Conjecture predict that the degree of the colored Jones polynomial of a knot is matched by the boundary slope and the Euler characteristic of some essential surfaces in the knot complement. By solving a problem of quadratic integer programming to find the maximal degree and using the Hatcher-Oertel edgepath system to find the corresponding essential surface, we verify the Slope Conjectures for a family of 3-string Montesinos knots satisfying certain conditions.

关键词： Slope conjecture colored Jones polynomial quadratic integer programming boundary slope incompressible surface

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