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020 _a9783319761923
_9978-3-319-76192-3
024 7 _a10.1007/978-3-319-76192-3
_2doi
050 4 _aTS1-2301
072 7 _aTGP
_2bicssc
072 7 _aTEC020000
_2bisacsh
072 7 _aTGP
_2thema
082 0 4 _a670
_223
100 1 _aFrench, Mark.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_951124
245 1 0 _aFundamentals of Optimization
_h[electronic resource] :
_bMethods, Minimum Principles, and Applications for Making Things Better /
_cby Mark French.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXIV, 249 p. 246 illus., 170 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aOptimization: The Big Ideas -- Getting Started in Optimization: Problems with a Single Variable -- Minimum Principles - Optimization in the Fabric of the Universe -- Problems with More Than One Variable -- Constraints – Placing Limits on the Solution -- General Conditions for Solving Optimization Problem – Karush Kuhn Tucker Conditions -- Discrete Variables -- Aerospace Applications -- Structural Optimization -- Multi-objective Optimization -- Appendix A - Calculus Refresher -- Appendix B - Test Functions -- Appendix C - Solving Optimization Problems using MATLAB.-.
520 _aThis textbook is for readers new or returning to the practice of optimization whose interest in the subject may relate to a wide range of products and processes. Rooted in the idea of “minimum principles,” the book introduces the reader to the analytical tools needed to apply optimization practices to an array of single- and multi-variable problems. While comprehensive and rigorous, the treatment requires no more than a basic understanding of technical math and how to display mathematical results visually. It presents a group of simple, robust methods and illustrates their use in clearly-defined examples. Distinct from the majority of optimization books on the market intended for a mathematically sophisticated audience who might want to develop their own new methods of optimization or do research in the field, this volume fills the void in instructional material for those who need to understand the basic ideas. The text emerged from a set of applications-driven lecture notes used in optimization courses the author has taught for over 25 years. The book is class-tested and refined based on student feedback, devoid of unnecessary abstraction, and ideal for students and practitioners from across the spectrum of engineering disciplines. It provides context through practical examples and sections describing commercial application of optimization ideas, such as how containerized freight and changing sea routes have been used to continually reduce the cost of moving freight across oceans. It also features 2D and 3D plots and an appendix illustrating the most widely used MATLAB optimization functions. Facilitates a solid grasp of the core concepts in optimization for students with no more than a background in basic technical math (derivatives); Maximizes reader understanding by focusing on a select group of simple, robust methods; Reinforces concepts with many numerical examples done in MathCAD clearly showing the intermediate calculations along with final results; Provides context through practical examples, including discussions of how optimization is used in commercial applications; Illustrates results graphically.
650 0 _aManufactures.
_931642
650 0 _aAerospace engineering.
_96033
650 0 _aAstronautics.
_951125
650 0 _aTransportation engineering.
_93560
650 0 _aTraffic engineering.
_915334
650 0 _aIndustrial Management.
_95847
650 0 _aSecurity systems.
_931879
650 0 _aEngineering mathematics.
_93254
650 0 _aEngineering—Data processing.
_931556
650 1 4 _aMachines, Tools, Processes.
_931645
650 2 4 _aAerospace Technology and Astronautics.
_951126
650 2 4 _aTransportation Technology and Traffic Engineering.
_932448
650 2 4 _aIndustrial Management.
_95847
650 2 4 _aSecurity Science and Technology.
_931884
650 2 4 _aMathematical and Computational Engineering Applications.
_931559
710 2 _aSpringerLink (Online service)
_951127
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319761916
776 0 8 _iPrinted edition:
_z9783319761930
776 0 8 _iPrinted edition:
_z9783030094263
856 4 0 _uhttps://doi.org/10.1007/978-3-319-76192-3
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c78716
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