• Fri frakt över 249 kr
  • •
  • Snabba leveranser
  • •
  • Billiga böcker
Kundservice

Du är på sajten för privatpersoner.

Företag, bibliotek eller offentlig verksamhet?

Du handlar på classic.bokus.com, där alla dina funktioner finns intakta.
Till classic.bokus.com
Bokus logotyp. Gå till startsidan.
  • Erbjudanden
  • Nyheter
  • Student
  • Topplistor
  • Barn & ungdom
  • Bokus Play
  • E-böcker
  • Pocketböcker
  • Spel & pussel

10% rabatt på allt med kod: NYSTART10 →

Sidfot

Mina sidor

    Hjälp

    • Kundservice
    • Vanliga frågor och svar
    • Frakt och leverans
    • Retur vid ångerrätt
    • Reklamera vara
    • Betalning
    • Köpvillkor
    • Allmänna villkor
    • Information om webbplatsens tillgänglighet

    Om Bokus

    • Om oss
    • Pressrum
    • För studenter
    • För företag
    • För bibliotek och offentlig verksamhet
    • För leverantörer
    • Hållbarhet

    Populärt

    • Aktuella erbjudanden
    • Presentkort
    • Studentlitteratur
    • Nya böcker
    • Topplistor
    • Signerade böcker
    • Engelska böcker

    Inspiration

    • Boktips
    • BookTok
    • Populära bokserier
    • Barnbokskaraktärer
    • Populära författare
    Logotyp för Bokus
    Följ oss på Facebook (extern länk)Följ oss på Instagram (extern länk)Följ oss på YouTube (extern länk)Följ oss på TikTok (extern länk)
    bokus @ CookiesAnpassa cookiesIntegritetspolicyKöpvillkor
    Till Citymail hemsida (extern länk)Till Budbee hemsida (extern länk)Till Postnord hemsida (extern länk)Till Schenker hemsida (extern länk)Till Early Bird hemsida (extern länk)Till Walleys hemsida (extern länk)
    1. Naturvetenskap och teknik
    2. Teknik och industri
    3. Teknik: allmänt

    Engineering Optimization

    Methods and Applications

    AvA. Ravindran,Ken M. Ragsdell

    Inbunden, Engelska, 2006

    1 992 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    The classic introduction to engineering optimization theory and practice--now expanded and updated Engineering optimization helps engineers zero in on the most effective, efficient solutions to problems. This text provides a practical, real-world understanding of engineering optimization. Rather than belaboring underlying proofs and mathematical derivations, it emphasizes optimization methodology, focusing on techniques and stratagems relevant to engineering applications in design, operations, and analysis. It surveys diverse optimization methods, ranging from those applicable to the minimization of a single-variable function to those most suitable for large-scale, nonlinear constrained problems. New material covered includes the duality theory, interior point methods for solving LP problems, the generalized Lagrange multiplier method and generalization of convex functions, and goal programming for solving multi-objective optimization problems. A practical, hands-on reference and text, Engineering Optimization, Second Edition covers:* Practical issues, such as model formulation, implementation, starting point generation, and more* Current, state-of-the-art optimization software* Three engineering case studies plus numerous examples from chemical, industrial, and mechanical engineering* Both classical methods and new techniques, such as successive quadratic programming, interior point methods, and goal programming Excellent for self-study and as a reference for engineering professionals, this Second Edition is also ideal for senior and graduate courses on engineering optimization, including television and online instruction, as well as for in-plant training.

    Produktinformation

    • Utgivningsdatum:2006-06-16
    • Mått:165 x 242 x 40 mm
    • Vikt:1 100 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:688
    • Upplaga:2
    • Förlag:John Wiley & Sons Inc
    • ISBN:9780471558149

    Utforska kategorier

    • Teknik: allmänt inom Naturvetenskap och teknik
    • Maskinteknik och material inom Naturvetenskap och teknik

    Mer om författaren

    A. RAVINDRAN, PhD, is Professor of Industrial and Manufacturing Engineering at Penn State University in University Park, Pennsylvania. K. M. RAGSDELL, PhD, is Professor of Engineering Management at the University of Missouri in Rolla, Missouri. G. V. REKLAITIS, PhD, is Edward W. Comings Professor of Chemical Engineering at Purdue University in West Lafayette, Indiana.

    Innehållsförteckning

    • Preface. 1 Introduction to Optimization. 1.1 Requirements for the Application of Optimization Methods. 1.2 Applications of Optimization in Engineering. 1.3 Structure of Optimization Problems. 1.4 Scope of This Book. References. 2 Functions of a Single Variable. 2.1 Properties of Single-Variable Functions. 2.2 Optimality Criteria. 2.3 Region Elimination Methods. 2.4 Polynomial Approximation or Point Estimation Methods. 2.5 Methods Requiring Derivatives. 2.6 Comparison of Methods. 2.7 Summary. References. Problems. 3 Functions of Several Variables. 3.1 Optimality Criteria. 3.2 Direct-Search Methods. 3.3 Gradient-Based Methods. 3.4 Comparison of Methods and Numerical Results. 3.5 Summary. References. Problems. 4 Linear Programming. 4.1 Formulation of Linear Programming Models. 4.2 Graphical Solution of Linear Programs in Two Variables. 4.3 Linear Program in Standard Form. 4.5 Computer Solution of Linear Programs. 4.5.1 Computer Codes. 4.6 Sensitivity Analysis in Linear Programming. 4.7 Applications. 4.8 Additional Topics in Linear Programming. 4.9 Summary. References. Problems. 5 Constrained Optimality Criteria. 5.1 Equality-Constrained Problems. 5.2 Lagrange Multipliers. 5.3 Economic Interpretation of Lagrange Multipliers. 5.4 Kuhn-Tucker Conditions. 5.5 Kuhn-Tucker Theorems. 5.6 Saddlepoint Conditions. 5.7 Second-Order Optimality Conditions. 5.8 Generalized Lagrange Multiplier Method. 5.9 Generalization of Convex Functions. 5.10 Summary. References. Problems. 6 Transformation Methods. 6.1 Penalty Concept. 6.2 Algorithms, Codes, and Other Contributions. 6.3 Method of Multipliers. 6.4 Summary. References. Problems. 7 Constrained Direct Search. 7.1 Problem Preparation. 7.2 Adaptations of Unconstrained Search Methods. 7.3 Random-Search Methods. 7.4 Summary. References. Problems. 8 Linearization Methods for Constrained Problems. 8.1 Direct Use of Successive Linear Programs. 8.2 Separable Programming. 8.3 Summary. References. Problems. 9 Direction Generation Methods Based on Linearization. 9.1 Method of Feasible Directions. 9.2 Simplex Extensions for Linearly Constrained Problems. 9.3 Generalized Reduced Gradient Method. 9.4 Design Application. 9.5 Summary. References. Problems. 10 Quadratic Approximation Methods for Constrained Problems. 10.1 Direct Quadratic Approximation. 10.2 Quadratic Approximation of the Lagrangian Function. 10.3 Variable Metric Methods for Constrained Optimization. 10.4 Discussion. 10.5 Summary. References. Problems. 11 Structured Problems and Algorithms. 11.1 Integer Programming. 11.2 Quadratic Programming. 11.3 Complementary Pivot Problems. 11.4 Goal Programming. 11.5 Summary. References. Problems. 12 Comparison of Constrained Optimization Methods. 12.1 Software Availability. 12.2 A Comparison Philosophy. 12.3 Brief History of Classical Comparative Experiments. 12.4 Summary. References. 13 Strategies for Optimization Studies. 13.1 Model Formulation. 13.2 Problem Implementation. 13.3 Solution Evaluation. 13.4 Summary. References. Problems. 14 Engineering Case Studies. 14.1 Optimal Location of Coal-Blending Plants by Mixed-Integer Programming. 14.2 Optimization of an Ethylene Glycol-Ethylene Oxide Process. 14.3 Optimal Design of a Compressed Air Energy Storage System. 14.4 Summary. References. Appendix A Review of Linear Algebra. A.1 Set Theory. A.2 Vectors. A.3 Matrices. A.3.1 Matrix Operations. A.3.2 Determinant of a Square Matrix. A.3.3 Inverse of a Matrix. A.3.4 Condition of a Matrix. A.3.5 Sparse Matrix. A.4 Quadratic Forms. A.4.1 Principal Minor. A.4.2 Completing the Square. A.5 Convex Sets. Appendix B Convex and Concave Functions. Appendix C Gauss-Jordan Elimination Scheme. Author Index. Subject Index.