Linear programming

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Linear programming (LP, or linear optimization) is a mathematical method for determining a way to achieve the best outcome (such as maximum profit or lowest cost) in a given mathematical model for some list of requirements represented as linear relationships. (Wikipedia.org)






Conferences related to Linear programming

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2016 IEEE 55th IEEE Conference on Decision and Control (CDC)

The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.

  • 2014 IEEE 53rd Annual Conference on Decision and Control (CDC)

    Largest annual conference in control theory and its applications. Areas covered all applied math, communication, control, aerospace, biology, etc.

  • 2013 IEEE 52nd Annual Conference on Decision and Control (CDC)

    The 52nd IEEE Conference on Decision and Control will be held Tuesday through Friday, December 10-13, 2013 at the Congress Centre in Firenze, Italy. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss the latest advancements of the discipline, shape its future directions, and promote its diffusion among the scientific community at large. The 52nd CDC will feature the presentation of contributed and invited papers, as well as tutorial sessions and workshops. The CDC is hosted by the IEEE Control Systems Society (CSS), and is organized in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).

  • 2012 IEEE 51st Annual Conference on Decision and Control (CDC)

    The conference discusses advances in theory, design and application of control systems. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the control systems from analysis and design through simulation and hardware. Its scope shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organiz

  • 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC 2011)

    This conference is dedicated to the advancement of the theory and practice of systems and control, bringing together an international community of researchers and practitioners to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.

  • 2010 49th IEEE Conference on Decision and Control (CDC)

    Theory and applications of control theory and control systems technology

  • 2009 Joint 48th IEEE Conference on Decision and Control (CDC) and 28th Chinese Control Conference (CCC)

    This conference is dedicated to the advancement of the theory and practice of systems and control, bringing together an international community of researchers and practitioners to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.

  • 2008 47th IEEE Conference on Decision and Control (CDC)

    The CDC is the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control, bringing together an international community of researchers and practitioners to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, automatic control, and related areas.


2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy theory and foundations; stability of fuzzy systems; fuzzy methods and algorithms; fuzzy image, speech and signal processing; multimedia; fuzzy hardware and architectures; data mining.

  • 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy theory and foundations; stability of fuzzy systems; fuzzy methods and algorithms; fuzzy image, speech and signal processing; multimedia; fuzzy hardware and architectures; data mining.

  • 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

    FSKD is an international forum on fuzzy systems and knowledge discovery. Specific topics include fuzzy theory and foundations; stability of fuzzy systems; fuzzy methods and algorithms; fuzzy image, speech and signal processing; multimedia; fuzzy hardware and architectures; data mining.


2012 Eighth International Conference on Computational Intelligence and Security (CIS)

CIS'12 provides a platform to explore the potential applications of CI models, algorithms and technologies to IS. Definitely, the subjects of CIS'12 conference, e.g. data minging, pattern recognition, machine learning, image processing, web application, and so forth, are closely related to the IEEE Computer Society's fields of interest.

  • 2008 International Conference on Computational Intelligence and Security (CIS 2008)

    International Conference on Computational Intelligence and Security (CIS) is a major annual international conference to bring together researchers, engineers, developers and practitioners from academia and industry working in all areas of two crucial fields in information processing: computational intelligence (CI) and information security (IS), to share the experience, and exchange and cross-fertilize ideas. In particular, the series of CIS conference provides an ideal platform to explore the potential app

  • 2007 International Conference on Computational Intelligence and Security (CIS 2007)

    International Conference on Computational Intelligence and Security (CIS) is a major annual international conference to bring together researchers, engineers, developers and practitioners from academia and industry working in all areas of two crucial fields in information processing: computational intelligence (CI) and information security (IS), to share the experience, and exchange and cross-fertilize ideas.

  • 2006 International Conference on Computational Intelligence and Security (CIS 2006)


2010 IEEE 2nd International Advance Computing Conference (IACC 2010)

Organizations and Institutions are competing to take leads in different areas of advance computing. Due to increasing complexity and size of problems the importance of this area has grown tremendously. The problems which were out of bounds to the computer scientists are now being solved using advance computing technologies. It has opened the flood gates for new research and innovations. In this endeavor we have taken an initiative to provide a common platform for all who are involved in this field.

  • 2009 IEEE International Advance Computing Conference (IACC 2009)

    In Computer Science the problem complexity and size is increasing. The Projects are becomingincreasingly difficult and huge in volume. Therefore the area of advance computing techniques in terms of efficient algorithms and reliable computing technologies is becoming of utmostimportance. This conference will work towards bridging the gap regarding the solution of the latest problems and the available techniques and technologies.



Periodicals related to Linear programming

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Information Theory, IEEE Transactions on

The fundamental nature of the communication process; storage, transmission and utilization of information; coding and decoding of digital and analog communication transmissions; study of random interference and information-bearing signals; and the development of information-theoretic techniques in diverse areas, including data communication and recording systems, communication networks, cryptography, detection systems, pattern recognition, learning, and automata.


Neural Networks, IEEE Transactions on

Devoted to the science and technology of neural networks, which disclose significant technical knowledge, exploratory developments, and applications of neural networks from biology to software to hardware. Emphasis is on artificial neural networks.


Selected Areas in Communications, IEEE Journal on

All telecommunications, including telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space, and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; communication theory; and wireless communications.


Systems, Man, and Cybernetics, Part B, IEEE Transactions on

The scope of the IEEE Transactions on Systems, Man and Cybernetics Part B: Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or between machines, humans, and organizations. The scope of Part B includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, ...



Most published Xplore authors for Linear programming

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Xplore Articles related to Linear programming

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Automatic Fuzzy Clustering Based on Adaptive Multi-Objective Differential Evolution for Remote Sensing Imagery

Yanfei Zhong; Shuai Zhang; Liangpei Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013

Traditional automatic fuzzy clustering methods can obtain the optimal number of clusters by maximizing or minimizing one single-objective function using validity indexes. However, the effectiveness of these methods depends on the selection of the validity indexes, and one single-objective function may not provide satisfactory results because of the complexity of remote sensing images. For instance, the same land types may ...


Efficient Privacy-Preserving Outsourcing of Large-Scale Convex Separable Programming for Smart Cities

Weixian Liao; Wei Du; Sergio Salinas; Pan Li 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 2016

One of the most salient features of smart city is to utilize big data to make our lives more convenient and more intelligent. This is usually achieved through solving a series of large-scale common and fundamental problems such as linear systems of equations, linear programs, etc. However, it is a very challenging task for resource-limited clients and small companies to ...


Discriminative non-negative matrix factorization with majorization-minimization

Li Li; Hirokazu Kameoka; Shoji Makino 2017 Hands-free Speech Communications and Microphone Arrays (HSCMA), 2017

Non-negative matrix factorization (NMF) is a powerful approach to single channel audio source separation. In a supervised setting, NMF is first applied to train the basis spectra of each sound source. At test time, NMF is applied to the spectrogram of a mixture signal using the pretrained spectra. The source signals can then be separated out using a Wiener filter. ...


A generalized discriminative training framework for system combination

Yuuki Tachioka; Shinji Watanabe; Jonathan Le Roux; John R. Hershey 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 2013

This paper proposes a generalized discriminative training framework for system combination, which encompasses acoustic modeling (Gaussian mixture models and deep neural networks) and discriminative feature transformation. To improve the performance by combining base systems with complementary systems, complementary systems should have reasonably good performance while tending to have different outputs compared with the base system. Although it is difficult to ...


Tracking of piecewise constant references for constrained nonlinear systems

L. Chisci; P. Falugi; G. Zappa 2003 European Control Conference (ECC), 2003

The paper addresses tracking of a piecewise constant reference for a nonlinear system subject to control and/or state constraints. The proposed controller, called dual-mode, extends to the nonlinear case an approach formerly introduced for linear systems. The dual-mode controller is based on the knowledge of the set of feasible state-setpoint pairs and operates in two different modes: as a regulator ...


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Educational Resources on Linear programming

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eLearning

Automatic Fuzzy Clustering Based on Adaptive Multi-Objective Differential Evolution for Remote Sensing Imagery

Yanfei Zhong; Shuai Zhang; Liangpei Zhang IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013

Traditional automatic fuzzy clustering methods can obtain the optimal number of clusters by maximizing or minimizing one single-objective function using validity indexes. However, the effectiveness of these methods depends on the selection of the validity indexes, and one single-objective function may not provide satisfactory results because of the complexity of remote sensing images. For instance, the same land types may ...


Efficient Privacy-Preserving Outsourcing of Large-Scale Convex Separable Programming for Smart Cities

Weixian Liao; Wei Du; Sergio Salinas; Pan Li 2016 IEEE 18th International Conference on High Performance Computing and Communications; IEEE 14th International Conference on Smart City; IEEE 2nd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 2016

One of the most salient features of smart city is to utilize big data to make our lives more convenient and more intelligent. This is usually achieved through solving a series of large-scale common and fundamental problems such as linear systems of equations, linear programs, etc. However, it is a very challenging task for resource-limited clients and small companies to ...


Discriminative non-negative matrix factorization with majorization-minimization

Li Li; Hirokazu Kameoka; Shoji Makino 2017 Hands-free Speech Communications and Microphone Arrays (HSCMA), 2017

Non-negative matrix factorization (NMF) is a powerful approach to single channel audio source separation. In a supervised setting, NMF is first applied to train the basis spectra of each sound source. At test time, NMF is applied to the spectrogram of a mixture signal using the pretrained spectra. The source signals can then be separated out using a Wiener filter. ...


A generalized discriminative training framework for system combination

Yuuki Tachioka; Shinji Watanabe; Jonathan Le Roux; John R. Hershey 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, 2013

This paper proposes a generalized discriminative training framework for system combination, which encompasses acoustic modeling (Gaussian mixture models and deep neural networks) and discriminative feature transformation. To improve the performance by combining base systems with complementary systems, complementary systems should have reasonably good performance while tending to have different outputs compared with the base system. Although it is difficult to ...


Tracking of piecewise constant references for constrained nonlinear systems

L. Chisci; P. Falugi; G. Zappa 2003 European Control Conference (ECC), 2003

The paper addresses tracking of a piecewise constant reference for a nonlinear system subject to control and/or state constraints. The proposed controller, called dual-mode, extends to the nonlinear case an approach formerly introduced for linear systems. The dual-mode controller is based on the knowledge of the set of feasible state-setpoint pairs and operates in two different modes: as a regulator ...


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IEEE-USA E-Books

  • Generalized Support Vector Machines

    This chapter contains sections titled: Introduction, GSVM: The General Support Vector Machine, Quadratic Programming Support Vector Machines, Linear Programming Support Vector Machines, A Simple Illustrative Example, Conclusion, Acknowledgments

  • SteadyState Security Regions

    This chapter contains sections titled: Introduction Security Corridors Traditional Expansion Method Enhanced Expansion Method Fuzzy Set and Linear Programming Appendix: Linear Programming References

  • Reactive Power Optimization

    This chapter contains sections titled: Introduction Classic Method for Reactive Power Dispatch Linear Programming Method of VAR Optimization Interior Point Method for VAR Optimization Problem NLONN Approach VAR Optimization by Evolutionary Algorithm VAR Optimization by Particle Swarm Optimization Algorithm Reactive Power Pricing Calculation References

  • Solution of Equations, Inequalities, and Linear Programs

    This chapter contains sections titled: Extreme Values, Relative Maximum and Minimum Concave and Convex Functions Solution of Linear Equation Systems Linear Optimization Problems Linear Programs and Convex Sets - Relation Linear Programs Illustration of the Simplex Method Solution of Linear Programs Using Excel Solver Transportation Problems Duality in Linear Programming Exercise Problems

  • PerformanceDriven Compaction for Analog Integrated Circuits

    This paper describes a new approach to layout compaction of analog integrated circuits which respects _all_ of the performance and technology constraints necessary to guarantee proper analog circuit functionality. Our approach consists of two stages: a _fast_ constraint graph critical path algorithm followed by a _general_ linear programming algorithm. Circuit performance is guaranteed by mapping high-level performance constraints to low-level bounds on parasitics and then to minimum spacing constraints between adjacent nets.

  • Optimal Reconfiguration of Electrical Distribution Network

    This chapter contains sections titled: Introduction Mathematical Model of DNRC Heuristic Methods Rule-Based Comprehensive Approach Mixed-Integer Linear Programming Approach Application of GA to DNRC Multiobjective Evolution Programming to DNRC Genetic Algorithm Based on Matroid Theory References

  • Robust Ensemble Learning

    This chapter contains sections titled: Introduction, Boosting and the Linear Programming Solution, υ-Algorithms, Experiments, Conclusion, Acknowledgments

  • Modeling CrossLayer Interaction Using Inverse Optimization

    In this chapter, we proposed the use of the inverse shortest paths problem as a method to characterize the effect of congestion on routing protocols in MANETs, and demonstrated solutions of the resulting linear programming problem that are compatible with observations in the simulated network.

  • Post Global Routing Crosstalk Synthesis

    For the generation of a risk-free layout solution of a chip, crosstalk synthesis should be pursued at various stages in the routing process. This paper proposes a post global routing crosstalk optimization approach, which to our knowledge, is the first to estimate and reduce crosstalk risk at the global routing level. It consists of two parts: region-based crosstalk risk estimation and crosstalk risk reduction at the global routing level. In Part One, crosstalk risk graphs are first introduced for each routing region representing its current crosstalk situation. The crosstalk risk of each region, which indicates whether a risk-free routing solution of the region is possible, is then quantitatively defined and estimated using a graph-based approach. In Part Two, the risk tolerance bound of each net is partitioned appropriately among its routing regions via integer linear programming for accurate (minimized) crosstalk risk estimation. If high risk regions still exist after bound partitioning, net ripping-up and rerouting is applied to reduce their crosstalk risks. At the end of the entire optimization process, a risk-free global routing solution is obtained together with partitions of nets' risk tolerance bounds which reflect the current crosstalk situation of the chip. These can greatly facilitate the generation of a risk-free final solution at later stages in the layout process. The proposed approach has been implemented and tested on CBL/NCSU benchmarks and the experimental results are very promising.

  • About the Author

    The ever-growing number of new telecommunications technologies, along with the rapid growth of data networks and cable television systems has created a demand for sound network planning. In one concise volume, this book offers professionals in telecommunications and networking and graduate students an introduction to the theory underlying the interdisciplinary field of network planning, a critical aspect of network management that integrates planning telecommunications and data networks. In PLANNING TELECOMMUNICATIONS NETWORKS you will learn about the mathematical theory behind network planning, including an accessible treatment of linear programming and graph algorithms. Other featured topics cover: Reliability theory for network planning Recent software advances in databases, expert systems, object-oriented programming, data mining and data visualization Latest developments in new optimization techniques such as tabu search, simulated annealing, genetic algorithms, and neural networks Complete with homework problems, this text offers you a broad overview of network planning to begin your exploration of this emerging field. Sponsored by: IEEE Communications Society. An Instructor's Manual presenting detailed solutions to all the problems in the book is available upon request from the Wiley Makerting Department.



Standards related to Linear programming

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