LEADER 04685nam 22007455 450 001 9910300107403321 005 20251116195845.0 010 $a3-319-77586-3 024 7 $a10.1007/978-3-319-77586-9 035 $a(CKB)4100000004243804 035 $a(DE-He213)978-3-319-77586-9 035 $a(MiAaPQ)EBC6314419 035 $a(PPN)227402685 035 $a(EXLCZ)994100000004243804 100 $a20180502d2018 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPractical Mathematical Optimization $eBasic Optimization Theory and Gradient-Based Algorithms /$fby Jan A Snyman, Daniel N Wilke 205 $a2nd ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XXVI, 372 p. 81 illus., 17 illus. in color.) 225 1 $aSpringer Optimization and Its Applications,$x1931-6828 ;$v133 311 08$a3-319-77585-5 327 $a1.Introduction -- 2.Line search descent methods for unconstrained minimization.-3. Standard methods for constrained optimization.-4. Basic Example Problems -- 5. Some Basic Optimization Theorems -- 6. New gradient-based trajectory and approximation methods -- 7. Surrogate Models -- 8. Gradient-only solution strategies -- 9. Practical computational optimization using Python -- Appendix -- Index. 330 $aThis textbook presents a wide range of tools for a course in mathematical optimization for upper undergraduate and graduate students in mathematics, engineering, computer science, and other applied sciences. Basic optimization principles are presented with emphasis on gradient-based numerical optimization strategies and algorithms for solving both smooth and noisy discontinuous optimization problems. Attention is also paid to the difficulties of expense of function evaluations and the existence of multiple minima that often unnecessarily inhibit the use of gradient-based methods. This second edition addresses further advancements of gradient-only optimization strategies to handle discontinuities in objective functions. New chapters discuss the construction of surrogate models as well as new gradient-only solution strategies and numerical optimization using Python. A special Python module is electronically available (via springerlink) that makes the new algorithms featured in the text easily accessible and directly applicable. Numerical examples and exercises are included to encourage senior- to graduate-level students to plan, execute, and reflect on numerical investigations. By gaining a deep understanding of the conceptual material presented, students, scientists, and engineers will be able to develop systematic and scientific numerical investigative skills. . 410 0$aSpringer Optimization and Its Applications,$x1931-6828 ;$v133 606 $aMathematical optimization 606 $aAlgorithms 606 $aOperations research 606 $aManagement science 606 $aNumerical analysis 606 $aComputer software 606 $aFunctions of real variables 606 $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008 606 $aAlgorithms$3https://scigraph.springernature.com/ontologies/product-market-codes/M14018 606 $aOperations Research, Management Science$3https://scigraph.springernature.com/ontologies/product-market-codes/M26024 606 $aNumerical Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/M14050 606 $aMathematical Software$3https://scigraph.springernature.com/ontologies/product-market-codes/M14042 606 $aReal Functions$3https://scigraph.springernature.com/ontologies/product-market-codes/M12171 615 0$aMathematical optimization. 615 0$aAlgorithms. 615 0$aOperations research. 615 0$aManagement science. 615 0$aNumerical analysis. 615 0$aComputer software. 615 0$aFunctions of real variables. 615 14$aOptimization. 615 24$aAlgorithms. 615 24$aOperations Research, Management Science. 615 24$aNumerical Analysis. 615 24$aMathematical Software. 615 24$aReal Functions. 676 $a519.3 700 $aSnyman$b Jan A.$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767881 702 $aWilke$b Daniel N.$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910300107403321 996 $aPractical Mathematical Optimization$92102301 997 $aUNINA