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PLANNC: a projected Lagrangian based implementation for constrained nonlinear network flow problems

Mon, 10/15/2007 - 17:58 — admin
Publication TypeConference Paper
Year of Publication2001
AuthorsHeredia, F. J.
Conference Name20h IFIP TC7 Conference on System Modelling and Optimization
Conference Date23-27/07/2001
Conference LocationTrier, Germany.
Type of WorkContributed oral presentation
Key Wordsnonlinear network flows; nonlinear side constraints; research
AbstractRecents numerical experiments show that the resolution of the Nonlinear network Flow problem with side Constraints (NFC) can be significantly sped up, when the side constraints are linear, by specialised codes based on a conjunction of primal partitioning techniques and active set methods. A natural extension of these methods one is to be used into a Projected Lagrangian Algorithm (PLA). A specialised (PLA) will solve the general (NFC) problem through the optimization of a sequence of (NFC) with linear side constraints, taking benefit of the efficiency of the linear side constraints codes. The description of this methodology will be presented together with the preliminary numerical results.
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Using modeling languages for the complementary suppression problem through network flow models

Mon, 10/15/2007 - 17:49 — admin
Publication TypeConference Paper
Year of Publication2001
AuthorsCastro, J.; Heredia, F.J.
Conference Name2nd Joint UNECE/EUROSTAT Work Session on Statistical Data Confidentiality
Conference DateMarch 2001
Conference LocationSkopje, Republic of Macedonia.
Type of WorkInvited oral contribution.
Key Wordsresearch; complementary supression problem; network flows; statistical data confidentiality
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Tutorial on Nonlinear Optimization

Mon, 10/15/2007 - 17:46 — admin
Publication TypeConference Paper
Year of Publication2002
AuthorsHeredia, F. J.
Conference Name1BWSA, First Barcelona Workshop on Survival Analysis
Conference Date12-14/06/2002
Conference LocationUniversitat Politècnica de Catalunya, Barcelona, Spain.
Type of WorkTutorial
Key Wordsresearch; nonlinear optimization
AbstractThe purpose of this tutorial is top offer an overview of the most successful optimization methods used nowadays, and how these methods can be helpful solving the problems that arise in statistics. We will be focused on nonlinear optimization, either unconstrained and constrained, as these are the kind op optimization problems that generally appears in the statistics field.
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The radar multiplier method: a two-phase approach for large scale nonlinear combinatorial optimization problems

Mon, 10/15/2007 - 17:38 — admin
Publication TypeConference Paper
Year of Publication2003
AuthorsHeredia, F. J.; Beltran, C.
Conference Name 21th IFIP TC7 Conference on System Modelling and Optimization
Pagination92
Conference Date21-25/07/2003
PublisherINRIA
Conference LocationSophia Antipolis, France
EditorJ. Cagnol; J.P. Zolesio
Type of WorkContributed oral presentation
ISBN Number2-7261-1253-6
Key Wordsaugmented lagrangian relaxation; generalized unit commitment; radar multiplier method; research
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Generalized Unit Commitment

Mon, 10/15/2007 - 12:22 — admin
Publication TypeConference Paper
Year of Publication2004
AuthorsHeredia, F. J.; Beltran, C.
Conference NameApplied Mathematical Programming and Modellization (APMOD 2004)
Conference Date21-23/06/2004
Conference LocationBrunel University, Uxbridge, UK.
Type of WorkInvited oral presentation
Key Wordsaugmented lagrangian relaxation; generalized unit commitment; radar multiplier method; research
AbstractThe Generalized Unit Commitment problem (GUC) extends the unit commitment problem by adding the transmission network. A full-network modelization of the GUC problem is presented. In this model, all non-binary variables of the problem can be represented as flows of the so called Hydro-Thermal-Transmission Network (HTTN), including those representing incremental and decremental spinning reserve. The result is a large scale nonlinear mixed optimization problem that is solved with the Radar Multiplier method, a novel two-phase dual technique based on augmented Lagrangian relaxation and variable duplication. The computational implementation of the proposed model and method, both in FORTRAN and AMPL, are described. The numerical solution of several instances of the GUC problem will be presented and discussed, showing the capability of the model and solution technique to cope with real-world instances of the GUC problem.
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Optimal Short-Term Strategies for a Generation Company in the MIBEL

Mon, 09/24/2007 - 18:29 — admin
Publication TypeConference Paper
Year of Publication2006
AuthorsCorchero, C.; Heredia, F. J.
Conference NameAPMOD 2006: Applied Mathematical Programming and Modellization
Conference Date19-21/06/06
Conference LocationMadrid
EditorUniversidad Rey Juan carlos, Universidad Pontificia de Comillas
Type of WorkContributed session
Key Wordsstochastic programming; electricity markets; day-ahead market; future contracts; research
AbstractMIBEL, the future Spanish and Portuguese electricity market, is expected to start in 2007 and one of the most important changes will be the creation of short-term futures markets, such as daily and weekly futures contracts. This new framework will require important changes in the short term optimization strategies of the generation companies. We propose a methodology to coordinate the day-ahead market and the new daily futures market proposed in the MIBEL. This coordination is particularly important in physical futures contracts; they imply the obligation to supply energy and could change the optimal power planning. The methodology is based on stochastic mixed-integer programming and gives the optimal bid in the futures markets as long as the simultaneous optimization for power planning production and day-ahead market bidding for the thermal units of a price-taker generation company. The approach presented is stochastic because of the uncertainty of the spot and futures market prices. We use time series techniques to model the market prices and we introduce them in the optimization model by an optimally generated scenario tree. The implementation is done with a modelling language. Implementation details and some first computational experiences for small cases are presented.
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Numerical implementation and computational results of nonlinear network optimization with linear side constraints

Mon, 09/17/2007 - 23:09 — admin
Publication TypeBook Chapter
Year of Publication1991
AuthorsHeredia, F. J.; Nabona, N.
EditorP. Kall
Book TitleSystem Modelling and Optimization
PublisherSpringer Verlag
Key WordsNonlinear network flows
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Optimum Short-Term Hydrothermal Schedulling with Spinning Reserve through Network Flows

Mon, 09/17/2007 - 18:34 — admin
Publication TypeJournal Article
Year of Publication1995
AuthorsHeredia, F. J.; Nabona, N.
Journal TitleIEEE Trans. on Power Systems
Volume10
Issue3
Pages10
Start Page1642
PublisherThe Institue of Electrical and Electronic Engineering
ISSN Number0885-8950
Key Wordsnonlinear network flows; side constraints; power systems; short-term hydrothermal OPF; spinning reserve; research; paper
AbstractOptimizing the thermal production of electricity in the short term in an integrated power system when a thermal unit commitment has been decided means coordinating hydro and thermal generation in order to obtain the minimum thermal generation costs over the time period under study. Fundamental constraints to be satisfied are the covering of each hourly load and satisfaction of spinning reserve requirements and transmission capacity limits. A nonlinear network flow model with linear side constraints with no decomposition into hydro and thermal subproblems was used to solve the hydrothermal scheduling. Hydrogeneration is linearized with respect to network variables and a novel thermal generation and transmission network is introduced. Computational results are reported
URLClick Here
DOIhttp://dx.doi.org/10.1109/59.466476
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Spring School 2007. Stochastic Programming: theory and applications

Sun, 04/15/2007 - 19:13 — admin
Publication TypeConference/School/Seminar attendance
Year of Publication2007
AuthorsHeredia, F. J.
Event TypeSchool
Conference OrganiserDepartment of Mathematics, Computing and Applications. Università degli studi di Bergamo
Conference Dates10-20/04/2007
Conference LocationBergamo, Italy
Key WordsResearch, Stochastic Programming
AbstractThe initiative is oriented to researchers, doctoral students and practitioners with a general aim to attract a significant audience to a key and rapidly growing area of mathematical programming. The school aims also at establishing a qualified venue to enhance and promote the understanding by young scientists of the potentials of applied stochastic optimisation in areas such as finance, production planning, energy, telecommunications and clarify to leading practitioners the current state of the art in the development of stochastic optimisation techniques. The proposal comes at a point in which the potentials of stochastic programming techniques in applied decision theory are becoming fully recognised in the industry, and the demand for advanced education programmes in this area is growing.
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