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Convex optimization algorithms / Dimitri P. Bertsekas
| Convex optimization algorithms / Dimitri P. Bertsekas |
| Autore | Bertsekas, Dimitri P. |
| Pubbl/distr/stampa | Belmont, Mass. : Athena Scientific, c2015 |
| Descrizione fisica | xii, 564 p. : ill. ; 24 cm |
| Disciplina | 519.7 |
| Soggetto topico |
Convex programming
Mathematical optimization Convex functions |
| ISBN | 9781886529281 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991002765769707536 |
Bertsekas, Dimitri P.
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| Belmont, Mass. : Athena Scientific, c2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Interior-point polynomial algorithms in convex programming / Yurii Nesterov and Arkadii Nemirovskii
| Interior-point polynomial algorithms in convex programming / Yurii Nesterov and Arkadii Nemirovskii |
| Autore | Nesterov, IU. E. |
| Pubbl/distr/stampa | Philadelphia : SIAM (Society for Industrial and Applied Mathematics), c1994 |
| Descrizione fisica | ix, 405 p. ; 27 cm. |
| Disciplina | 519.76 |
| Altri autori (Persone) | Nemirovskii, Arkadii Semenovich |
| Collana | Siam studies in applied mathematics ; 13 |
| Soggetto topico |
Convex programming
Programming |
| ISBN | 0898713196 |
| Classificazione | AMS 90C25 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991001005799707536 |
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Nesterov, IU. E.
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| Philadelphia : SIAM (Society for Industrial and Applied Mathematics), c1994 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Mathematical programming for power systems operation : from theory to applications in Python / / Alejandro Garcés Ruiz
| Mathematical programming for power systems operation : from theory to applications in Python / / Alejandro Garcés Ruiz |
| Autore | Ruiz Alejandro Garcés <1981-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons Inc., , [2022] |
| Descrizione fisica | 1 online resource (298 pages) |
| Disciplina | 621.31 |
| Collana | IEEE Press Ser. |
| Soggetto topico |
Electric power systems - Mathematical models
Convex programming Python (Computer program language) |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-119-74728-7
1-119-74729-5 1-119-74727-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Mathematical Programming for Power Systems Operation -- Contents -- Acknowledgment -- Introduction -- 1 Power systems operation -- 1.1 Mathematical programming for power systems operation -- 1.2 Continuous models -- 1.2.1 Economic and environmental dispatch -- 1.2.2 Hydrothermal dispatch -- 1.2.3 Effect of the grid constraints -- 1.2.4 Optimal power flow -- 1.2.5 Hosting capacity -- 1.2.6 Demand-side management -- 1.2.7 Energy storage management -- 1.2.8 State estimation and grid identification -- 1.3 Binary problems in power systems operation -- 1.3.1 Unit commitment -- 1.3.2 Optimal placement of distributed generation and capacitors -- 1.3.3 Primary feeder reconfiguration and topology identification -- 1.3.4 Phase balancing -- 1.4 Real-time implementation -- 1.5 Using Python -- Part I Mathematical programming -- 2 A brief introduction to mathematical optimization -- 2.1 About sets and functions -- 2.2 Norms -- 2.3 Global and local optimum -- 2.4 Maximum and minimum values of continuous functions -- 2.5 The gradient method -- 2.6 Lagrange multipliers -- 2.7 The Newton's method -- 2.8 Further readings -- 2.9 Exercises -- 3 Convex optimization -- 3.1 Convex sets -- 3.2 Convex functions -- 3.3 Convex optimization problems -- 3.4 Global optimum and uniqueness of the solution -- 3.5 Duality -- 3.6 Further readings -- 3.7 Exercises -- 4 Convex Programming in Python -- 4.1 Python for convex optimization -- 4.2 Linear programming -- 4.3 Quadratic forms -- 4.4 Semidefinite matrices -- 4.5 Solving quadratic programming problems -- 4.6 Complex variables -- 4.7 What is inside the box? -- 4.8 Mixed-integer programming problems -- 4.9 Transforming MINLP into MILP -- 4.10 Further readings -- 4.11 Exercises -- 5 Conic optimization -- 5.1 Convex cones -- 5.2 Second-order cone optimization -- 5.2.1 Duality in SOC problems -- 5.3 Semidefinite programming.
5.3.1 Trace, determinant, and the Shur complement -- 5.3.2 Cone of semidefinite matrices -- 5.3.3 Duality in SDP -- 5.4 Semidefinite approximations -- 5.5 Polynomial optimization -- 5.6 Further readings -- 5.7 Exercises -- 6 Robust optimization -- 6.1 Stochastic vs robust optimization -- 6.1.1 Stochastic approach -- 6.1.2 Robust approach -- 6.2 Polyhedral uncertainty -- 6.3 Linear problems with norm uncertainty -- 6.4 Defining the uncertainty set -- 6.5 Further readings -- 6.6 Exercises -- Part II Power systems operation -- 7 Economic dispatch of thermal units -- 7.1 Economic dispatch -- 7.2 Environmental dispatch -- 7.3 Effect of the grid -- 7.4 Loss equation -- 7.5 Further readings -- 7.6 Exercises -- 8 Unit commitment -- 8.1 Problem definition -- 8.2 Basic unit commitment model -- 8.3 Additional constraints -- 8.4 Effect of the grid -- 8.5 Further readings -- 8.6 Exercises -- 9 Hydrothermal scheduling -- 9.1 Short-term hydrothermal coordination -- 9.2 Basic hydrothermal coordination -- 9.3 Non-linear models -- 9.4 Hydraulic chains -- 9.5 Pumped hydroelectric storage -- 9.6 Further readings -- 9.7 Exercises -- 10 Optimal power flow -- 10.1 OPF in power distribution grids -- 10.1.1 A brief review of power flow analysis -- 10.2 Complex linearization -- 10.2.1 Sequential linearization -- 10.2.2 Exponential models of the load -- 10.3 Second-order cone approximation -- 10.4 Semidefinite approximation -- 10.5 Further readings -- 10.6 Exercises -- 11 Active distribution networks -- 11.1 Modern distribution networks -- 11.2 Primary feeder reconfiguration -- 11.3 Optimal placement of capacitors -- 11.4 Optimal placement of distributed generation -- 11.5 Hosting capacity of solar energy -- 11.6 Harmonics and reactive power compensation -- 11.7 Further readings -- 11.8 Exercises -- 12 State estimation and grid identification -- 12.1 Measurement units. 12.2 State estimation -- 12.3 Topology identification -- 12.4 Ybus estimation -- 12.5 Load model estimation -- 12.6 Further readings -- 12.7 Exercises -- 13 Demand-side management -- 13.1 Shifting loads -- 13.2 Phase balancing -- 13.3 Energy storage management -- 13.4 Further readings -- 13.5 Exercises -- A The nodal admittance matrix -- B Complex linearization -- C Some Python examples -- C.1 Basic Python -- C.2 NumPy -- C.3 MatplotLib -- C.4 Pandas -- Bibliography -- Index -- EULA. |
| Record Nr. | UNINA-9910555012803321 |
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Ruiz Alejandro Garcés <1981->
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| Hoboken, New Jersey : , : John Wiley & Sons Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mathematical programming for power systems operation : from theory to applications in Python / / Alejandro Garcés Ruiz
| Mathematical programming for power systems operation : from theory to applications in Python / / Alejandro Garcés Ruiz |
| Autore | Ruiz Alejandro Garcés <1981-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons Inc., , [2022] |
| Descrizione fisica | 1 online resource (298 pages) |
| Disciplina | 621.31 |
| Collana | IEEE Press |
| Soggetto topico |
Electric power systems - Mathematical models
Convex programming Python (Computer program language) |
| ISBN |
1-119-74728-7
1-119-74729-5 1-119-74727-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Mathematical Programming for Power Systems Operation -- Contents -- Acknowledgment -- Introduction -- 1 Power systems operation -- 1.1 Mathematical programming for power systems operation -- 1.2 Continuous models -- 1.2.1 Economic and environmental dispatch -- 1.2.2 Hydrothermal dispatch -- 1.2.3 Effect of the grid constraints -- 1.2.4 Optimal power flow -- 1.2.5 Hosting capacity -- 1.2.6 Demand-side management -- 1.2.7 Energy storage management -- 1.2.8 State estimation and grid identification -- 1.3 Binary problems in power systems operation -- 1.3.1 Unit commitment -- 1.3.2 Optimal placement of distributed generation and capacitors -- 1.3.3 Primary feeder reconfiguration and topology identification -- 1.3.4 Phase balancing -- 1.4 Real-time implementation -- 1.5 Using Python -- Part I Mathematical programming -- 2 A brief introduction to mathematical optimization -- 2.1 About sets and functions -- 2.2 Norms -- 2.3 Global and local optimum -- 2.4 Maximum and minimum values of continuous functions -- 2.5 The gradient method -- 2.6 Lagrange multipliers -- 2.7 The Newton's method -- 2.8 Further readings -- 2.9 Exercises -- 3 Convex optimization -- 3.1 Convex sets -- 3.2 Convex functions -- 3.3 Convex optimization problems -- 3.4 Global optimum and uniqueness of the solution -- 3.5 Duality -- 3.6 Further readings -- 3.7 Exercises -- 4 Convex Programming in Python -- 4.1 Python for convex optimization -- 4.2 Linear programming -- 4.3 Quadratic forms -- 4.4 Semidefinite matrices -- 4.5 Solving quadratic programming problems -- 4.6 Complex variables -- 4.7 What is inside the box? -- 4.8 Mixed-integer programming problems -- 4.9 Transforming MINLP into MILP -- 4.10 Further readings -- 4.11 Exercises -- 5 Conic optimization -- 5.1 Convex cones -- 5.2 Second-order cone optimization -- 5.2.1 Duality in SOC problems -- 5.3 Semidefinite programming.
5.3.1 Trace, determinant, and the Shur complement -- 5.3.2 Cone of semidefinite matrices -- 5.3.3 Duality in SDP -- 5.4 Semidefinite approximations -- 5.5 Polynomial optimization -- 5.6 Further readings -- 5.7 Exercises -- 6 Robust optimization -- 6.1 Stochastic vs robust optimization -- 6.1.1 Stochastic approach -- 6.1.2 Robust approach -- 6.2 Polyhedral uncertainty -- 6.3 Linear problems with norm uncertainty -- 6.4 Defining the uncertainty set -- 6.5 Further readings -- 6.6 Exercises -- Part II Power systems operation -- 7 Economic dispatch of thermal units -- 7.1 Economic dispatch -- 7.2 Environmental dispatch -- 7.3 Effect of the grid -- 7.4 Loss equation -- 7.5 Further readings -- 7.6 Exercises -- 8 Unit commitment -- 8.1 Problem definition -- 8.2 Basic unit commitment model -- 8.3 Additional constraints -- 8.4 Effect of the grid -- 8.5 Further readings -- 8.6 Exercises -- 9 Hydrothermal scheduling -- 9.1 Short-term hydrothermal coordination -- 9.2 Basic hydrothermal coordination -- 9.3 Non-linear models -- 9.4 Hydraulic chains -- 9.5 Pumped hydroelectric storage -- 9.6 Further readings -- 9.7 Exercises -- 10 Optimal power flow -- 10.1 OPF in power distribution grids -- 10.1.1 A brief review of power flow analysis -- 10.2 Complex linearization -- 10.2.1 Sequential linearization -- 10.2.2 Exponential models of the load -- 10.3 Second-order cone approximation -- 10.4 Semidefinite approximation -- 10.5 Further readings -- 10.6 Exercises -- 11 Active distribution networks -- 11.1 Modern distribution networks -- 11.2 Primary feeder reconfiguration -- 11.3 Optimal placement of capacitors -- 11.4 Optimal placement of distributed generation -- 11.5 Hosting capacity of solar energy -- 11.6 Harmonics and reactive power compensation -- 11.7 Further readings -- 11.8 Exercises -- 12 State estimation and grid identification -- 12.1 Measurement units. 12.2 State estimation -- 12.3 Topology identification -- 12.4 Ybus estimation -- 12.5 Load model estimation -- 12.6 Further readings -- 12.7 Exercises -- 13 Demand-side management -- 13.1 Shifting loads -- 13.2 Phase balancing -- 13.3 Energy storage management -- 13.4 Further readings -- 13.5 Exercises -- A The nodal admittance matrix -- B Complex linearization -- C Some Python examples -- C.1 Basic Python -- C.2 NumPy -- C.3 MatplotLib -- C.4 Pandas -- Bibliography -- Index -- EULA. |
| Record Nr. | UNINA-9910677364103321 |
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Ruiz Alejandro Garcés <1981->
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| Hoboken, New Jersey : , : John Wiley & Sons Inc., , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Mathematical techniques of optimization, control, and decision / J. P. Aubin, A. Bensoussan, I. Ekeland, editors
| Mathematical techniques of optimization, control, and decision / J. P. Aubin, A. Bensoussan, I. Ekeland, editors |
| Autore | Aubin, Jean Pierre |
| Pubbl/distr/stampa | Boston : Birkhäuser, 1981 |
| Descrizione fisica | viii, 212 p. : ill. ; 24 cm. |
| Disciplina |
510
519 |
| Altri autori (Persone) |
Bensoussan, Alain
Ekeland, Ivar |
| Collana | Annals of the C.E.R.E.M.A.D.E |
| Soggetto topico |
Calculus of variations
Collections of articles of miscellaneous specific content Control theory Convex programming Decision-making Mathematical optimization Ordinary differential equations Partial differential equations |
| ISBN | 3764330325 |
| Classificazione |
AMS 00B15
AMS 34-06 AMS 35-06 AMS 49-06 AMS 90C25 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991001118889707536 |
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Aubin, Jean Pierre
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| Boston : Birkhäuser, 1981 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Metodo di ottimizzazione convessa: algoritmo di Frank-Wolfe. Tesi di laurea / laureanda Erica Antermite ; relat. Paolo Nobili
| Metodo di ottimizzazione convessa: algoritmo di Frank-Wolfe. Tesi di laurea / laureanda Erica Antermite ; relat. Paolo Nobili |
| Autore | Antermite, Erica |
| Pubbl/distr/stampa | Lecce : Università del Salento. Facoltà di Scienze MM.FF.NN. Corso di laurea in Matematica, a.a. 2017-18 |
| Descrizione fisica | 26 p. ; 30 cm |
| Disciplina | 510 |
| Altri autori (Persone) | Nobili, Paolo |
| Soggetto topico |
Convex programming
Method of reduced gradient type |
| Classificazione |
AMS 90C25
AMS 90C52 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Record Nr. | UNISALENTO-991003579429707536 |
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Antermite, Erica
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| Lecce : Università del Salento. Facoltà di Scienze MM.FF.NN. Corso di laurea in Matematica, a.a. 2017-18 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Network flows and monotropic optimization / R.T. Rockafellar
| Network flows and monotropic optimization / R.T. Rockafellar |
| Autore | Rockafellar, R. Tyrrell, 1935- |
| Pubbl/distr/stampa | Belmont, Mau : Athena Scientific, c1998 |
| Descrizione fisica | xiii, 616 p. : ill. ; 24 cm |
| Disciplina | 519.7 |
| Collana | Series on optimization, computation, and control ; 8 |
| Soggetto topico |
Network analysis (Planning)
Convex programming Linear programming |
| ISBN | 188652906X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991003610599707536 |
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Rockafellar, R. Tyrrell, 1935-
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| Belmont, Mau : Athena Scientific, c1998 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Optimality in nonlinear programming : a feasible directions approach / A. Ben-Israel, A. Ben-Tal, S. Zlobec
| Optimality in nonlinear programming : a feasible directions approach / A. Ben-Israel, A. Ben-Tal, S. Zlobec |
| Autore | Ben-Israel, Adi |
| Descrizione fisica | xii, 144 p. : ill. ; 24 cm. |
| Disciplina | 519.76 |
| Altri autori (Persone) |
Ben-Tal, A.
Zlobec, S.author |
| Collana | Pure and applied mathematics. A wiley-interscience series of texts, monographs & tracts, ISSN 00798185 |
| Soggetto topico |
Convex programming
Mathematical optimization Nonlinear programming |
| ISBN | 0471080578 |
| Classificazione |
AMS 90C25
AMS 90C26 AMS 90C30 T57.8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991001208199707536 |
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Ben-Israel, Adi
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| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Ottimizzazione delle operazioni di carica dei veicoli elettrici. Tesi di laurea / laureando Filandro Savino ; relatore Paolo Nobili
| Ottimizzazione delle operazioni di carica dei veicoli elettrici. Tesi di laurea / laureando Filandro Savino ; relatore Paolo Nobili |
| Autore | Savino, Filandro |
| Pubbl/distr/stampa | Lecce : Università del Salento. Facoltà di Scienze MM. FF. NN. Corso di Laurea Magistrale in Matematica, a.a. 2012-13 |
| Descrizione fisica | 80 p. ; 30 cm |
| Altri autori (Persone) | Nobili, Paolo |
| Soggetto topico |
Convex programming
Combinatorial optimization |
| Classificazione |
AMS 90C25
AMS 90C27 AMS 90C90 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Record Nr. | UNISALENTO-991002386749707536 |
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Savino, Filandro
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| Lecce : Università del Salento. Facoltà di Scienze MM. FF. NN. Corso di Laurea Magistrale in Matematica, a.a. 2012-13 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Problèmes de minimax via l'analyse convexe et les inégalités variationnelles : théorie et algorithmes / A. Auslender
| Problèmes de minimax via l'analyse convexe et les inégalités variationnelles : théorie et algorithmes / A. Auslender |
| Autore | Auslender, Alfred |
| Pubbl/distr/stampa | Berlin ; New York : Springer-Verlag, 1972 |
| Descrizione fisica | vii, 132 p. ; 26 cm. |
| Disciplina | 515.64 |
| Collana | Lecture notes in economics and mathematical systems, 0075-8442 ; 77 |
| Soggetto topico |
Convex programming
Mathematical optimization Maxima and minima |
| ISBN | 3540060790 |
| Classificazione | AMS 49J35 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNISALENTO-991001254199707536 |
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Auslender, Alfred
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| Berlin ; New York : Springer-Verlag, 1972 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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