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International Joint Conference on Neural Networks (IJCNN)

作者： Paredes, Gonzalo E. Vargas, Luis S. Univ Chile Dept Elect Engn Santiago Chile

ISBN: (纸本)9781467314909

This paper present a novel method to perform clustering of time-series and static data. The method, named Circle-Clustering (CirCle), could be classified as a partition method that uses criteria from SVM and hierarchical methods to perform a better clustering. Different heuristic clustering techniques were tested against the CirCle method by using data sets from UCI Machine Learning Repository. In all tests, CirCle obtained good results and outperformed most of clustering techniques considered in this work. In addition, CirCle was tested against others heuristic techniques considering time-series data from electric feeders in Santiago, Chile's capital city. The optimal solution of the min-cut clustering optimization problem was solved in order to identify the optimal solution for 883 datasets. The results show that the proposed method obtains an average of 81% of well-classified samples in all datasets. Also, as compared to other algorithms, CirCle made a better classification in 98.7% of the datasets as compared to the Model-Base Best BIC. As compared to K-means, Robust K-means and Ward's methods the new algorithm classified better in nearly 68% of the datasets.

关键词： component heuristic clustering techniques mixed integer programming

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Optimal Scheduling of Storage Devices for Building Energy Saving

Optimal Scheduling of Storage Devices for Building Energy Sa...

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10th World Congress on Intelligent Control and Automation (WCICA)

作者： Xu, Zhanbo Jia, Qing-Shan Guan, Xiaohong Wu, Jiang Wang, Dai Chen, Siyun Xi An Jiao Tong Univ SKLMS Lab Xian Shaanxi Provinc Peoples R China Xi An Jiao Tong Univ MOEKLINNS Lab Xian Shaanxi Provinc Peoples R China Tsinghua Univ TNLIST Dept Automat CFINS Beijing Peoples R China

ISBN: (纸本)9781467313988

An intelligent building energy system which has power grid, autonomous generators, renewable energy resources, storage devices, and controllable loads has been proposed. In this paper, we consider an allocation and scheduling problem of electrical and thermal storage devices together with other devices in building energy system to minimize the overall cost while satisfying the occupants demand. The above problem is formulated as a mixed integer programming problem. The CPLEX solver is used to solve the proposed problem. By the proposed method, we can fix the types of storage devices and allocate the capacity of the fixed storage devices with demand profiles and their investment cost. The performance analysis of storage devices is demonstrated using numerical cases.

关键词： building energy saving storage devices optimal capacities and types mixed integer programming

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Numerical Comparison of Optimal Charging Schemes for Electric Vehicles

Numerical Comparison of Optimal Charging Schemes for Electri...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： You, S. Hu, J. Pedersen, A. B. Andersen, P. B. Rasmussen, C. N. Cha, S. Tech Univ Denmark Dept Elect Engn Ctr Elect Technol DK-2880 Lyngby Denmark

ISBN: (纸本)9781467327299

The optimal charging schemes for Electric vehicles (EV) generally differ from each other in the choice of charging periods and the possibility of performing vehicle-to-grid (V2G), and have different impacts on EV economics. Regarding these variations, this paper presents a numerical comparison of four different charging schemes, namely night charging, night charging with V2G, 24 hour charging and 24 hour charging with V2G, on the basis of real driving data and electricity price of Denmark in 2003. For all schemes, optimal charging plans with 5 minute resolution are derived through the solving of a mixed integer programming problem which aims to minimize the charging cost and meanwhile takes into account the users' driving needs and the practical limitations of the EV battery. In the post processing stage, the rainflow counting algorithm is implemented to assess the lifetime usage of a lithium-ion EV battery for the four charging schemes. The night charging scheme is found to be the cheapest solution after conducting an annual cost comparison.

关键词： Electric vehicle mixed integer programming optimal charging rainflow counting vehicle-to-grid V2G

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ALL OPTIMAL SOLUTIONS IN STDMA SCHEDULING

ALL OPTIMAL SOLUTIONS IN STDMA SCHEDULING

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20th European Signal Processing Conference (EUSIPCO)

作者： Quintas, Diogo Friderikos, Vasilis Kings Coll London Ctr Telecommun Res London WC2R 2LS England

ISBN: (纸本)9781467310680

In this paper we review different mixed integer programming formulations of the STDMA Scheduling problem and introduce a novel formulation. It is shown that the problem admits, in general, multiple optimal solutions - we propose an efficient cut generation procedure to construct all optimal schedules and investigate the properties of optimal schedules in two small networks.

关键词： mixed integer programming scheduling all optima physical interference

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Mathematical programming Model Concerning City and Urban Traffic

Mathematical Programming Model Concerning City and Urban Tra...

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6th International Conference on Soft Computing and Intelligent Systems (SCIS) / 13th International Symposium on Advanced Intelligence Systems (ISIS)

作者： Matsumoto, Takuya Inamoto, Tsutomu Tamaki, Hisashi Hyogo Prefectural Inst Technol Kobe Hyogo 6540037 Japan Kobe Univ Grad Sch Syst Informat Kobe Hyogo 6578501 Japan

ISBN: (纸本)9781467327435;9781467327428

The aim of our research is to acquire ideal images of city and urban traffic for various purpose. To achieve the aim, we propose optimization models which consist of city, mobilities and inhabitants. There are two models we are proposed from point of view of accuracy and computation time. One is relatively accurate but takes a lot of time to compute. The other is less accurate, however, larger problems can be computed than the former model. The former model could not solve practical size due to computational time. Through computational experiment using extreme evaluation values, validness of latter model is suggested.

关键词： optimization urban traffic mixed integer programming

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mixed n-step MIR inequalities, n-step conic MIR inequalities and a polyhedral study of single row facility layout problem

Mixed n-step MIR inequalities, n-step conic MIR inequalities...

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作者： Sanjeevi, Sujeevraja Texas A&M University

学位级别：Ph.D.

In this dissertation, we introduce new families of valid inequalities for general linear mixed integer programs (MIPs) and second-order conic MIPs (SOCMIPs) and establish several theoretical properties and computational effectiveness of these inequalities. First we introduce the mixed n-step mixed integer rounding (MIR) inequalities for a generalization of the mixing set which we refer to as the n-mixing set. The n-mixing set is a multi-constraint mixed integer set in which each constraint has n integer variables and a single continuous variable. We then show that mixed n-step MIR can generate multi-row valid inequalities for general MIPs and special structure MIPs, namely, multimodule capacitated lot-sizing and facility location problems. We also present the results of our computational experiments with the mixed n-step MIR inequalities on small MIPLIB instances and randomly generated multi-module lot-sizing instances which show that these inequalities are quite effective. Next, we introduce the n-step conic MIR inequalities for the so-called polyhedral second-order conic (PSOC) mixed integer sets. PSOC sets arise in the polyhedral reformulation of SOCMIPs. We first introduce the n-step conic MIR inequality for a PSOC set with n integer variables and prove that all the 1-step to n-step conic MIR inequalities are facet-defining for the convex hull of this set. We also provide necessary and sufficient conditions for the PSOC form of this inequality to be valid. Then, we use the aforementioned n-step conic MIR facet to derive the n-step conic MIR inequality for a general PSOC set and provide conditions for it to be facet-defining. We further show that the n-step conic MIR inequality for a general PSOC set strictly dominates the n-step MIR inequalities written for the two linear constraints that define the PSOC set. We also prove that the n-step MIR inequality for a linear mixed integer constraint is a special case of the n-step conic MIR inequality. Finally, we conduc

关键词： n-step MIR mixed n-step MIR mixing n-step conic MIR mixed integer programming multi-module capacitated lot-sizing multi-module capacitated facility location valid inequality facet polytope Thesis

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A new country risk index for emerging markets: A stochastic dominance approach

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JOURNAL OF EMPIRICAL FINANCE 2012年第5期19卷 741-761页

作者： Agliardi, Elettra Agliardi, Rossella Pinar, Mehmet Stengos, Thanasis Topaloglou, Nikolas Univ Bologna Dept Econ I-40126 Bologna Italy Rimini Ctr Econ Anal Rimini Italy Univ Bologna Dept Math I-40126 Bologna Italy Edge Hill Univ Business Sch Ormskirk L39 4QP Lancs England Univ Guelph Dept Econ Guelph ON N1G 2W1 Canada Athens Univ Econ & Business Dept Int European & Econ Studies GR-10434 Athens Greece

An optimal weighting scheme is proposed to construct economic, political and financial risk indices in emerging markets using an approach that relies on consistent tests for stochastic dominance efficiency. These tests are considered for a given risk index with respect to all possible indices constructed from a set of individual risk factors. The test statistics and the estimators are computed using mixed integer programming methods. We derive an economic. political and financial risk ranking of emerging countries. Finally, an overall risk index is constructed. One main result is that the financial risk is the leading contributor to sovereign risk in emerging markets followed by the economic and political risks. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Nonparametric stochastic dominance mixed integer programming Sovereign risk Emerging economies

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Semi-supervised learning using greedy max-cut

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2013年第1期14卷

作者： Kevin Murphy Bernhard Schölkopf Jun Wang Tony Jebara Shih-Fu Chang Google MPI for Intelligent Systems IBM T.J. Watson Research Center Yorktown Heights NY Department of Computer Science Columbia University New York NY Department of Electrical Engineering Columbia University New York NY

Graph-based semi-supervised learning (SSL) methods play an increasingly important role in practical machine learning systems, particularly in agnostic settings when no parametric information or other prior knowledge is available about the data distribution. Given the constructed graph represented by a weight matrix, transductive inference is used to propagate known labels to predict the values of all unlabeled vertices. Designing a robust label diffusion algorithm for such graphs is a widely studied problem and various methods have recently been suggested. Many of these can be formalized as regularized function estimation through the minimization of a quadratic cost. However, most existing label diffusion methods minimize a univariate cost with the classification function as the only variable of interest. Since the observed labels seed the diffusion process, such univariate frameworks are extremely sensitive to the initial label choice and any label noise. To alleviate the dependency on the initial observed labels, this article proposes a bivariate formulation for graph-based SSL, where both the binary label information and a continuous classification function are arguments of the optimization. This bivariate formulation is shown to be equivalent to a linearly constrained Max-Cut problem. Finally an efficient solution via greedy gradient Max-Cut (GGMC) is derived which gradually assigns unlabeled vertices to each class with minimum connectivity. Once convergence guarantees are established, this greedy Max-Cut based SSL is applied on both artificial and standard benchmark data sets where it obtains superior classification accuracy compared to existing state-of-the-art SSL methods. Moreover, GGMC shows robustness with respect to the graph construction method and maintains high accuracy over extensive experiments with various edge linking and weighting schemes.

关键词： bivariate formulation graph transduction greedy max-cut mixed integer programming semi-supervised learning

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A mixed integer programming model for advanced planning and scheduling (APS)

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第1期181卷 515-522页

作者： Chen, Kejia Ji, Ping Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Hong Kong Peoples R China

This paper presents a mixed integer programming (MIP) model which succeeds in a system integration of the production planning and shop floor scheduling problems. The proposed advanced planning and scheduling (APS) model explicitly considers capacity constraints, operation sequences, lead times and due dates in a multi-order environment. The objective of the model is to seek the minimum cost of both production idle time and tardiness or earliness penalty of an order. The output of the model is operation schedules with order starting time and finish time. Numerical result shows that the suggested APS model can favorably produce optimal schedules. (c) 2006 Elsevier B.V. All rights reserved.

关键词： scheduling MRP advanced planning and scheduling mixed integer programming

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Conflict analysis in mixed integer programming

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DISCRETE OPTIMIZATION 2007年第1期4卷 4-20页

作者： Achterberg, Tobias Konrad Zuse Zentrum Informat Tech Berlin Germany

Conflict analysis for infeasible subproblems is one of the key ingredients in modern SAT solvers. III contrast, it is common practice for today's mixed integer programming solvers to discard infeasible subproblems and the information they reveal. III this paper, we try to remedy this situation by generalizing SAT infeasibility analysis to mixed integer programming. We present heuristics for branch-and-cut solvers to generate valid inequalities from the Current infeasible subproblem and the associated branching information. SAT techniques can then be used to strengthen the resulting constraints. Extensive Computational experiments show the potential Of Our method. Conflict analysis greatly improves the performance oil particular models, while it does not interfere with the solving process on the other instances. In total, the number of required branching nodes oil general MIP instances was reduced by 18% in the geometric mean, and the solving time was reduced by 11%. On infeasible MIP arising in the context of chip verification and on a model for a particular combinatorial game, the number of nodes was reduced by 80%, thereby reducing the solving time by 50%. (c) 2006 Elsevier B.V. All rights reserved.

关键词： mixed integer programming branch-and-cut conflict analysis SAT infeasible mixed integer programming

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