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Application of a hybrid generation/utility assessment heuristic to a class of scheduling problems [[electronic resource] /] / Ann O. Heyward
| Application of a hybrid generation/utility assessment heuristic to a class of scheduling problems [[electronic resource] /] / Ann O. Heyward |
| Autore | Heyward Ann O |
| Pubbl/distr/stampa | Cleveland, Ohio : , : NASA, Lewis Research Center, , [1989] |
| Descrizione fisica | 1 online resource (10 pages) : illustrations |
| Collana | NASA technical memorandum |
| Soggetto topico |
Decision theory
Heuristic methods Problem solving Scheduling Sequencing Heuristic programming |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910701454803321 |
Heyward Ann O
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| Cleveland, Ohio : , : NASA, Lewis Research Center, , [1989] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Engineering optimization [[electronic resource] ] : an introduction with metaheuristic applications / / Xin-She Yang
| Engineering optimization [[electronic resource] ] : an introduction with metaheuristic applications / / Xin-She Yang |
| Autore | Yang Xin-She |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2010 |
| Descrizione fisica | 1 online resource (377 p.) |
| Disciplina | 620.001/5196 |
| Soggetto topico |
Heuristic programming
Mathematical optimization Engineering mathematics |
| ISBN |
1-282-70777-9
9786612707773 0-470-64042-1 0-470-64041-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Engineering Optimization: An Introduction with Metaheuristic Applications; CONTENTS; List of Figures; Preface; Acknowledgments; Introduction; PART I FOUNDATIONS OF OPTIMIZATION AND ALGORITHMS; 1 A Brief History of Optimization; 1.1 Before 1900; 1.2 Twentieth Century; 1.3 Heuristics and Metaheuristics; Exercises; 2 Engineering Optimization; 2.1 Optimization; 2.2 Type of Optimization; 2.3 Optimization Algorithms; 2.4 Metaheuristics; 2.5 Order Notation; 2.6 Algorithm Complexity; 2.7 No Free Lunch Theorems; Exercises; 3 Mathematical Foundations; 3.1 Upper and Lower Bounds; 3.2 Basic Calculus
3.3 Optimality3.3.1 Continuity and Smoothness; 3.3.2 Stationary Points; 3.3.3 Optimality Criteria; 3.4 Vector and Matrix Norms; 3.5 Eigenvalues and Definiteness; 3.5.1 Eigenvalues; 3.5.2 Definiteness; 3.6 Linear and Affine Functions; 3.6.1 Linear Functions; 3.6.2 Affine Functions; 3.6.3 Quadratic Form; 3.7 Gradient and Hessian Matrices; 3.7.1 Gradient; 3.7.2 Hessian; 3.7.3 Function approximations; 3.7.4 Optimality of multivariate functions; 3.8 Convexity; 3.8.1 Convex Set; 3.8.2 Convex Functions; Exercises; 4 Classic Optimization Methods I; 4.1 Unconstrained Optimization 4.2 Gradient-Based Methods4.2.1 Newton's Method; 4.2.2 Steepest Descent Method; 4.2.3 Line Search; 4.2.4 Conjugate Gradient Method; 4.3 Constrained Optimization; 4.4 Linear Programming; 4.5 Simplex Method; 4.5.1 Basic Procedure; 4.5.2 Augmented Form; 4.6 Nonlinear Optimization; 4.7 Penalty Method; 4.8 Lagrange Multipliers; 4.9 Karush-Kuhn-Tucker Conditions; Exercises; 5 Classic Optimization Methods II; 5.1 BFGS Method; 5.2 Nelder-Mead Method; 5.2.1 A Simplex; 5.2.2 Nelder-Mead Downhill Simplex; 5.3 Trust-Region Method; 5.4 Sequential Quadratic Programming; 5.4.1 Quadratic Programming 5.4.2 Sequential Quadratic ProgrammingExercises; 6 Convex Optimization; 6.1 KKT Conditions; 6.2 Convex Optimization Examples; 6.3 Equality Constrained Optimization; 6.4 Barrier Functions; 6.5 Interior-Point Methods; 6.6 Stochastic and Robust Optimization; Exercises; 7 Calculus of Variations; 7.1 Euler-Lagrange Equation; 7.1.1 Curvature; 7.1.2 Euler-Lagrange Equation; 7.2 Variations with Constraints; 7.3 Variations for Multiple Variables; 7.4 Optimal Control; 7.4.1 Control Problem; 7.4.2 Pontryagin's Principle; 7.4.3 Multiple Controls; 7.4.4 Stochastic Optimal Control; Exercises 8 Random Number Generators8.1 Linear Congruential Algorithms; 8.2 Uniform Distribution; 8.3 Other Distributions; 8.4 Metropolis Algorithms; Exercises; 9 Monte Carlo Methods; 9.1 Estimating π; 9.2 Monte Carlo Integration; 9.3 Importance of Sampling; Exercises; 10 Random Walk and Markov Chain; 10.1 Random Process; 10.2 Random Walk; 10.2.1 ID Random Walk; 10.2.2 Random Walk in Higher Dimensions; 10.3 Lévy Flights; 10.4 Markov Chain; 10.5 Markov Chain Monte Carlo; 10.5.1 Metropolis-Hastings Algorithms; 10.5.2 Random Walk; 10.6 Markov Chain and Optimisation; Exercises PART II METAHEURISTIC ALGORITHMS |
| Record Nr. | UNINA-9910140843303321 |
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Yang Xin-She
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| Hoboken, NJ, : Wiley, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Engineering optimization : an introduction with metaheuristic applications / / Xin-She Yang
| Engineering optimization : an introduction with metaheuristic applications / / Xin-She Yang |
| Autore | Yang Xin-She |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, NJ, : Wiley, c2010 |
| Descrizione fisica | 1 online resource (377 p.) |
| Disciplina | 620.001/5196 |
| Soggetto topico |
Heuristic programming
Mathematical optimization Engineering mathematics |
| ISBN |
9786612707773
9781282707771 1282707779 9780470640425 0470640421 9780470640418 0470640413 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Engineering Optimization: An Introduction with Metaheuristic Applications; CONTENTS; List of Figures; Preface; Acknowledgments; Introduction; PART I FOUNDATIONS OF OPTIMIZATION AND ALGORITHMS; 1 A Brief History of Optimization; 1.1 Before 1900; 1.2 Twentieth Century; 1.3 Heuristics and Metaheuristics; Exercises; 2 Engineering Optimization; 2.1 Optimization; 2.2 Type of Optimization; 2.3 Optimization Algorithms; 2.4 Metaheuristics; 2.5 Order Notation; 2.6 Algorithm Complexity; 2.7 No Free Lunch Theorems; Exercises; 3 Mathematical Foundations; 3.1 Upper and Lower Bounds; 3.2 Basic Calculus
3.3 Optimality3.3.1 Continuity and Smoothness; 3.3.2 Stationary Points; 3.3.3 Optimality Criteria; 3.4 Vector and Matrix Norms; 3.5 Eigenvalues and Definiteness; 3.5.1 Eigenvalues; 3.5.2 Definiteness; 3.6 Linear and Affine Functions; 3.6.1 Linear Functions; 3.6.2 Affine Functions; 3.6.3 Quadratic Form; 3.7 Gradient and Hessian Matrices; 3.7.1 Gradient; 3.7.2 Hessian; 3.7.3 Function approximations; 3.7.4 Optimality of multivariate functions; 3.8 Convexity; 3.8.1 Convex Set; 3.8.2 Convex Functions; Exercises; 4 Classic Optimization Methods I; 4.1 Unconstrained Optimization 4.2 Gradient-Based Methods4.2.1 Newton's Method; 4.2.2 Steepest Descent Method; 4.2.3 Line Search; 4.2.4 Conjugate Gradient Method; 4.3 Constrained Optimization; 4.4 Linear Programming; 4.5 Simplex Method; 4.5.1 Basic Procedure; 4.5.2 Augmented Form; 4.6 Nonlinear Optimization; 4.7 Penalty Method; 4.8 Lagrange Multipliers; 4.9 Karush-Kuhn-Tucker Conditions; Exercises; 5 Classic Optimization Methods II; 5.1 BFGS Method; 5.2 Nelder-Mead Method; 5.2.1 A Simplex; 5.2.2 Nelder-Mead Downhill Simplex; 5.3 Trust-Region Method; 5.4 Sequential Quadratic Programming; 5.4.1 Quadratic Programming 5.4.2 Sequential Quadratic ProgrammingExercises; 6 Convex Optimization; 6.1 KKT Conditions; 6.2 Convex Optimization Examples; 6.3 Equality Constrained Optimization; 6.4 Barrier Functions; 6.5 Interior-Point Methods; 6.6 Stochastic and Robust Optimization; Exercises; 7 Calculus of Variations; 7.1 Euler-Lagrange Equation; 7.1.1 Curvature; 7.1.2 Euler-Lagrange Equation; 7.2 Variations with Constraints; 7.3 Variations for Multiple Variables; 7.4 Optimal Control; 7.4.1 Control Problem; 7.4.2 Pontryagin's Principle; 7.4.3 Multiple Controls; 7.4.4 Stochastic Optimal Control; Exercises 8 Random Number Generators8.1 Linear Congruential Algorithms; 8.2 Uniform Distribution; 8.3 Other Distributions; 8.4 Metropolis Algorithms; Exercises; 9 Monte Carlo Methods; 9.1 Estimating π; 9.2 Monte Carlo Integration; 9.3 Importance of Sampling; Exercises; 10 Random Walk and Markov Chain; 10.1 Random Process; 10.2 Random Walk; 10.2.1 ID Random Walk; 10.2.2 Random Walk in Higher Dimensions; 10.3 Lévy Flights; 10.4 Markov Chain; 10.5 Markov Chain Monte Carlo; 10.5.1 Metropolis-Hastings Algorithms; 10.5.2 Random Walk; 10.6 Markov Chain and Optimisation; Exercises PART II METAHEURISTIC ALGORITHMS |
| Record Nr. | UNINA-9910814521403321 |
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Yang Xin-She
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| Hoboken, NJ, : Wiley, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Heuristic scheduling systems : with applications to production systems and project management / Thomas E. Morton and David W. Pentico
| Heuristic scheduling systems : with applications to production systems and project management / Thomas E. Morton and David W. Pentico |
| Autore | Morton, Thomas E., 1937- |
| Pubbl/distr/stampa | New York : Wiley, c1993 |
| Descrizione fisica | xiv, 695 p. : ill. ; 25 cm. + floppy |
| Disciplina | 658.5 |
| Altri autori (Persone) | Pentico, David W. |
| Collana | Wiley series in engineering & technology management |
| Soggetto topico |
Production control
Production scheduling Heuristic programming |
| ISBN | 0471578193 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISALENTO-991001521849707536 |
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Morton, Thomas E., 1937-
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| New York : Wiley, c1993 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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International journal of applied metaheuristic computing
| International journal of applied metaheuristic computing |
| Pubbl/distr/stampa | Hershey, PA, : IGI Publishing |
| Disciplina | 006.3 |
| Soggetto topico |
Heuristic programming
Mathematical optimization Neural networks (Computer science) |
| Soggetto genere / forma | Periodicals. |
| Soggetto non controllato | Operations Research |
| ISSN | 1947-8291 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | IJAMC |
| Record Nr. | UNISA-996546865403316 |
| Hershey, PA, : IGI Publishing | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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International journal of applied metaheuristic computing
| International journal of applied metaheuristic computing |
| Pubbl/distr/stampa | Hershey, PA, : IGI Publishing |
| Disciplina | 006.3 |
| Soggetto topico |
Heuristic programming
Mathematical optimization Neural networks (Computer science) |
| Soggetto genere / forma | Periodicals. |
| ISSN | 1947-8291 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | IJAMC |
| Record Nr. | UNINA-9910895758103321 |
| Hershey, PA, : IGI Publishing | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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ISMSI 2017 : proceedings of 2017 International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence : Hong Kong, March 25-27, 2017
| ISMSI 2017 : proceedings of 2017 International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence : Hong Kong, March 25-27, 2017 |
| Pubbl/distr/stampa | New York : , : ACM, , 2017 |
| Descrizione fisica | 1 online resource (171 pages) |
| Disciplina | 006.33 |
| Collana | ACM International Conference Proceedings Series |
| Soggetto topico |
Expert systems (Computer science)
Swarm intelligence Heuristic programming |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti |
International Conference on Intelligent Systems, Metaheuristics and Swarm Intelligence 2017
Proceedings of the 2017 International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence |
| Record Nr. | UNINA-9910375782903321 |
| New York : , : ACM, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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ISMSI 2021 : 5th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence : Victoria, Seychelles, April 10-11, 2021 / / Association for Computing Machinery
| ISMSI 2021 : 5th International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence : Victoria, Seychelles, April 10-11, 2021 / / Association for Computing Machinery |
| Pubbl/distr/stampa | New York, NY : , : The Association for Computing Machinery, , [2021] |
| Descrizione fisica | 1 online resource : illustrations |
| Disciplina | 006.33 |
| Collana | ACM international conference proceedings series |
| Soggetto topico |
Expert systems (Computer science)
Heuristic programming Neural networks (Computer science) Swarm intelligence |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910510447003321 |
| New York, NY : , : The Association for Computing Machinery, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Journal of heuristics
| Journal of heuristics |
| Pubbl/distr/stampa | [Dordrecht], : Kluwer Academic Publishers |
| Disciplina | 519.3 |
| Soggetto topico |
Heuristic programming
Programmation heuristique Heuristik Zeitschrift Online-Ressource |
| Soggetto genere / forma | Periodicals. |
| ISSN | 1572-9397 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996217674703316 |
| [Dordrecht], : Kluwer Academic Publishers | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Journal of heuristics
| Journal of heuristics |
| Pubbl/distr/stampa | [Dordrecht], : Kluwer Academic Publishers |
| Disciplina | 519.3 |
| Soggetto topico |
Heuristic programming
Programmation heuristique Heuristik Zeitschrift Online-Ressource Heurística |
| Soggetto genere / forma |
Periodicals.
Revistes electròniques. |
| ISSN | 1572-9397 |
| Formato | Materiale a stampa |
| Livello bibliografico | Periodico |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910145553203321 |
| [Dordrecht], : Kluwer Academic Publishers | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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