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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Room impulse response reshaping by joint optimization of multiple p-norm based criteria

Jan Ole Jungmann; Tiemin Mei; Stefan Goetze; Alfred Mertins 2011 19th European Signal Processing Conference, 2011

The purpose of room impulse response reshaping is usually to reduce reverberation and thus to improve the perceived quality of the received signal by prefiltering the source signal before it is played with a loudspeaker in a closed room or by postfiltering the recorded microphone signal. The utilization of an infinity- and/or p-norm based objective function in the time domain ...


An approach for object manipulation using cooperative agents

Qingguo Li; S. Payandeh Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., 2006

This paper explores a cooperative manipulation method for orienting and translating convex objects in the plane. The manipulation task is performed by two agents using the concept of "virtual fence". During the manipulation, each agent makes a point contact with the object, and two agents push together along a straight-line. One advantage of a virtual fence over physical fence is ...


Fast global scan matching for high-speed vehicle navigation

Tomonari Furukawa; Lakshitha Dantanarayana; Jason Ziglar; Ravindra Ranasinghe; Gamini Dissanayake 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 2015

This paper presents a fast global scan matching technique for high-speed vehicle navigation. The proposed grid-based scan-to-map matching technique collectively handles unprocessed scan points at each grid cell as a grid feature. The grid features are transformed and located in the global frame and updated every time a new scan is acquired. Since registered and updated are only grid features, ...


Optimal placement and sizing of multi distributed generators using teaching and learning based optimization

Phanindra kumar Ganivada; Chintham Venkaiah 2014 International Conference on Smart Electric Grid (ISEG), 2014

In this paper a new optimization algorithm TLBO (Teaching and Learning Based Optimization) has been implemented to solve optimal multi Distributed Generator (DG) placement problem. This problem has been formulated for minimization of loss, capacity release of transmission lines and voltage profile improvement. To reduce search space and computational burden optimization has been done in two stages first to find ...


A procurement model with material purchasing value analysis in construction supply chain

Huanhuan Gou; Zhenyuan Liu; Zheng Li 2011 Chinese Control and Decision Conference (CCDC), 2011

As the source of the modern enterprise value chain, purchasing value drives the value updated and added constantly. Based on construction supply chain, the origin of the purchasing value was analyzed from three dimensions which consist of materials value, suppliers value, and social value in this paper. A multi-objective linear programming model was proposed and solved by the fuzzy mathematics. ...


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Educational Resources on Linear programming

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eLearning

Room impulse response reshaping by joint optimization of multiple p-norm based criteria

Jan Ole Jungmann; Tiemin Mei; Stefan Goetze; Alfred Mertins 2011 19th European Signal Processing Conference, 2011

The purpose of room impulse response reshaping is usually to reduce reverberation and thus to improve the perceived quality of the received signal by prefiltering the source signal before it is played with a loudspeaker in a closed room or by postfiltering the recorded microphone signal. The utilization of an infinity- and/or p-norm based objective function in the time domain ...


An approach for object manipulation using cooperative agents

Qingguo Li; S. Payandeh Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., 2006

This paper explores a cooperative manipulation method for orienting and translating convex objects in the plane. The manipulation task is performed by two agents using the concept of "virtual fence". During the manipulation, each agent makes a point contact with the object, and two agents push together along a straight-line. One advantage of a virtual fence over physical fence is ...


Fast global scan matching for high-speed vehicle navigation

Tomonari Furukawa; Lakshitha Dantanarayana; Jason Ziglar; Ravindra Ranasinghe; Gamini Dissanayake 2015 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI), 2015

This paper presents a fast global scan matching technique for high-speed vehicle navigation. The proposed grid-based scan-to-map matching technique collectively handles unprocessed scan points at each grid cell as a grid feature. The grid features are transformed and located in the global frame and updated every time a new scan is acquired. Since registered and updated are only grid features, ...


Optimal placement and sizing of multi distributed generators using teaching and learning based optimization

Phanindra kumar Ganivada; Chintham Venkaiah 2014 International Conference on Smart Electric Grid (ISEG), 2014

In this paper a new optimization algorithm TLBO (Teaching and Learning Based Optimization) has been implemented to solve optimal multi Distributed Generator (DG) placement problem. This problem has been formulated for minimization of loss, capacity release of transmission lines and voltage profile improvement. To reduce search space and computational burden optimization has been done in two stages first to find ...


A procurement model with material purchasing value analysis in construction supply chain

Huanhuan Gou; Zhenyuan Liu; Zheng Li 2011 Chinese Control and Decision Conference (CCDC), 2011

As the source of the modern enterprise value chain, purchasing value drives the value updated and added constantly. Based on construction supply chain, the origin of the purchasing value was analyzed from three dimensions which consist of materials value, suppliers value, and social value in this paper. A multi-objective linear programming model was proposed and solved by the fuzzy mathematics. ...


More eLearning Resources

IEEE-USA E-Books

  • Global Inference for Entity and Relation Identification via Linear Programming Formulation

    This chapter contains sections titled: Introduction, The Relational Inference Problem, Integer Linear Programming Inference, Solving Integer Linear Programming, Experiments, Comparison with Other Inference Methods, Conclusion, Acknowledgments, References

  • Robust Ensemble Learning

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

  • No title

    In this book we give an overview of modeling techniques used to describe computer systems to mathematical optimization tools. We give a brief introduction to various classes of mathematical optimization frameworks with special focus on mixed integer linear programming which provides a good balance between solver time and expressiveness. We present four detailed case studies -- instruction set customization, data center resource management, spatial architecture scheduling, and resource allocation in tiled architectures -- showing how MILP can be used and quantifying by how much it outperforms traditional design exploration techniques. This book should help a skilled systems designer to learn techniques for using MILP in their problems, and the skilled optimization expert to understand the types of computer systems problems that MILP can be applied to.

  • 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.

  • SecurityConstrained Economic Dispatch

    This chapter contains sections titled: Introduction Linear Programming Method Quadratic Programming Method Network Flow Programming Method Nonlinear Convex Network Flow Programming Method Two-Stage Economic Dispatch Approach Security-Constrained ED by Genetic Algorithms Appendix: Network Flow Programming References

  • Optimal Power Flow

    This chapter contains sections titled: Introduction Newton Method Gradient Method Linear Programming OPF Modified Interior Point OPF OPF with Phase Shifter Multiple-Objectives OPF Particle Swarm Optimization for OPF References

  • Security-Constrained Economic Dispatch

    Security-constrained economic dispatch (SCED) is a simplified optimal power flow (OPF) problem. It is widely used in the power industry. This chapter introduces several major approaches to solve the SCED problem, such as linear programming (LP), network flow programming (NFP), and quadratic programming (QP). Then, nonlinear convex network flow programming (NLCNFP) and the genetic algorithm (GA) are added to tackle the SCED problem. It also provides the implementation details of these methods and a number of numerical examples. The chapter presents a new NLCNFP model of economic dispatch control (EDC), which is solved by a combination approach of QP and NFP. It also presents a two-stage economic dispatch (ED) approach according to the practical operation situation of power systems. The first stage involves the classic economic power dispatch without considering network loss. The second stage involves ED considering system power loss and network security constraints.

  • Association Schemes and Coding Theory

    This paper contains a survey of association scheme theory (with its algebraic and analytical aspects) and of its applications to coding theory (in a wide sense). It is mainly concerned with a class of subjects that involve the central notion of the distance distribution of a code. Special emphasis is put on the linear programming method, inspired by the MacWilliams transform. This produces upper bounds for the size of a code with a given minimum distance, and lower bounds for the size of a design with a given strength. The most specific results are obtained in the case where the underlying association scheme satisfies certain well-defined ?>polynomial properties;?> this leads one into the realm of orthogonal polynomial theory. In particular, some ?>universal bounds?> are derived for codes and designs in polynomial type association schemes. Throughout the paper, the main concepts, methods, and results are illustrated by two examples that are of major significance in classical coding theory, namely, the Hamming scheme and the Johnson scheme. Other topics that receive special attention are spherical codes and designs, and additive codes in translation schemes, including Z4 -additive binary codes.

  • 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.

  • Perceptron Learning and the Pocket Algorithm

    This chapter contains sections titled: 3.1 Perceptron Learning for Separable Sets of Training Examples, 3.2 the Pocket Algorithm for Nonseparable Sets of Training Examples, *3.3 Khachiyan's Linear Programming Algorithm, 3.4 Exercises, 3.5 Programming Projects



Standards related to Linear programming

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Jobs related to Linear programming

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