Skip to content
Register Sign in Wishlist

Principles of Optimal Design
Modeling and Computation

3rd Edition

$74.99 (X)

  • Date Published: January 2017
  • availability: Available
  • format: Hardback
  • isbn: 9781107132672

$ 74.99 (X)

Add to cart Add to wishlist

Other available formats:

Request examination copy

Instructors may request a copy of this title for examination

Product filter button
About the Authors
  • Design optimization is a standard concept in engineering design, and in other disciplines which utilize mathematical decision-making methods. This textbook focuses on the close relationship between a design problem's mathematical model and the solution-driven methods which optimize it. Along with extensive material on modeling problems, this book also features useful techniques for checking whether a model is suitable for computational treatment. Throughout, key concepts are discussed in the context of why and when a particular algorithm may be successful, and a large number of examples demonstrate the theory or method right after it is presented. This book also contains step-by-step instructions for executing a design optimization project - from building the problem statement to interpreting the computer results. All chapters contain exercises from which instructors can easily build quizzes, and a chapter on 'principles and practice' offers the reader tips and guidance based on the authors' vast research and instruction experience.

    • Includes extensive material on modeling design problems and unique techniques for checking whether the model is suitable for computational treatment before a numerical solution is attempted using a step-by-step approach
    • Contains a large number of simple examples that demonstrate theory or methods right after they are presented
    • Provides detailed instructions on how to execute a design optimization project from problem statement to interpretation of computer results
    Read more

    Reviews & endorsements

    'Principles of Optimal Design, third edition, offers an excellent combination of depth and breadth of fundamentals of mathematical modeling of systems design. Students and practitioners will find the textbook a great starting point to learn about the systems design methods and optimization theories from the fundamentals to the advanced numerical methods. The recent addition of the decomposition-based optimization method and analytical target cascading is a nice expansion to the traditional optimization methods. I use this textbook to teach graduate and advanced undergraduate students who have basic understanding of numerical analysis. Students appreciate the spectrum of contents and they become ready to apply what they learn from the textbook to complex systems design cases. I highly recommend the textbook.' Harrison Hyung, University of Illinois, Urbana-Champaign

    'Principles of Optimal Design has always been a well-structured textbook that introduces students to the fundamentals of optimal design while remaining accessible and enjoyable to read. The latest edition adds many brief but exciting glimpses of more advanced topics in optimization. These additions have transformed the book from a ‘foundation’ on which students can firmly stand to a ‘catapult’ that can propel them to exciting, new, and advanced topics in the broad discipline of optimal design.' Hosam Fathy, Penn State College of Engineering

    'This third edition brings to the reader an impressive array of new and useful topics in optimal design. For example, and among others, new chapters on non-gradient based methods and decomposition-based optimization (or multi-disciplinary optimization, MDO) have been added. The book can be used both as a textbook for a graduate level course in all engineering fields, but also as a must have reference material. I highly recommend it!' Shapour Azarm, University of Maryland

    'The Principles of Optimal Design, third edition, is an excellent first text for undergraduates and graduate students alike interested in gaining a firm grasp of practical design optimization methods. It blends the latest modeling techniques with a rigorous treatment of the mathematical analysis, allowing one to adeptly navigate the varied landscapes of modern design problems. From machine learning, automotive systems, financial portfolios, to even the modeling of human purchasing behavior, I have used this text to teach my students how to systematically apply the design process to a broad range of engineering problems.' George J. Delagrammatikas, The Cooper Union for the Advancement of Science and Art, New York

    'This book, almost thirty years after its first edition, remains the only comprehensive text on engineering design optimization. In our 'one-click' software era, it provides theory fundamentals that tend to be neglected, while complementing them with rigorous modeling and computation techniques. I cannot think of a better textbook for engineering optimization courses, including a plethora of excellent examples and exercises. The third edition is enhanced with new and extremely useful material on recent developments in derivative-free optimization and optimal system design.' Michael Kokkolaras, McGill University, Canada

    'I've found Principles of Optimal Design to be an excellent, comprehensive explanation of design optimization methods, grounded in rigorous mathematics, yet still accessible. The addition of a gradient-free optimization chapter is a welcome addition to the book.' John Whitefoot, University of Pittsburgh

    'I've recommended this book to several students. It's a great resource for students who need to use optimization for practical purposes, such as a senior project or an assignment at their co-op job. The book has a good balance between the underlying theory and the application of that theory to actual problems.' Diane Peters, University of Michigan

    See more reviews

    Customer reviews

    Not yet reviewed

    Be the first to review

    Review was not posted due to profanity


    , create a review

    (If you're not , sign out)

    Please enter the right captcha value
    Please enter a star rating.
    Your review must be a minimum of 12 words.

    How do you rate this item?


    Product details

    • Edition: 3rd Edition
    • Date Published: January 2017
    • format: Hardback
    • isbn: 9781107132672
    • length: 504 pages
    • dimensions: 254 x 196 x 28 mm
    • weight: 1.3kg
    • contains: 75 b/w illus.
    • availability: Available
  • Table of Contents

    1. Optimization models
    2. Model construction
    3. Model boundedness
    4. Interior optima
    5. Boundary optima
    6. Local computation
    7. Nongradient search
    8. Systems design
    9. Principles and practice
    Author index
    Subject index.

  • Resources for

    Principles of Optimal Design

    Panos Y. Papalambros, Douglass J. Wilde

    Find resources associated with this title

    Type Name Unlocked * Format Size

    Showing of

    Back to top

    This title is supported by one or more locked resources. Access to locked resources is granted exclusively by Cambridge University Press to instructors whose faculty status has been verified. To gain access to locked resources, instructors should sign in to or register for a Cambridge user account.

    Please use locked resources responsibly and exercise your professional discretion when choosing how you share these materials with your students. Other instructors may wish to use locked resources for assessment purposes and their usefulness is undermined when the source files (for example, solution manuals or test banks) are shared online or via social networks.

    Supplementary resources are subject to copyright. Instructors are permitted to view, print or download these resources for use in their teaching, but may not change them or use them for commercial gain.

    If you are having problems accessing these resources please contact

  • Authors

    Panos Y. Papalambros, University of Michigan, Ann Arbor
    Panos Y. Papalambros is the J. B. Angell Distinguished University Professor and the Donald C. Graham Professor of Engineering, and holds additional professorships in Mechanical Engineering, Art and Design, and Architecture at the University of Michigan. His research and teaching interests are in design science and design optimization. He is the author of more than 350 research publications. He served as the Chief Editor of the ASME Journal of Mechanical Design (2008–2012) and is the founding Chief Editor of the Design Science journal.

    Douglass J. Wilde, Stanford University, California
    Douglass J. Wilde is Professor Emeritus of Mechanical Engineering at Stanford University, California. He conducted research in optimization, computational geometry, and control theory. On retirement he began exploring student team building in design contests. In addition to previous editions of Principles of Optimal Design, he has written two books, Teamology (2009) and Jung's Personality Theory Quantified (2011).

Sorry, this resource is locked

Please register or sign in to request access. If you are having problems accessing these resources please email

Register Sign in
Please note that this file is password protected. You will be asked to input your password on the next screen.

» Proceed

You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner Please see the permission section of the catalogue page for details of the print & copy limits on our eBooks.

Continue ×

Continue ×

Continue ×
warning icon

Turn stock notifications on?

You must be signed in to your Cambridge account to turn product stock notifications on or off.

Sign in Create a Cambridge account arrow icon

Find content that relates to you

Join us online

This site uses cookies to improve your experience. Read more Close

Are you sure you want to delete your account?

This cannot be undone.


Thank you for your feedback which will help us improve our service.

If you requested a response, we will make sure to get back to you shortly.

Please fill in the required fields in your feedback submission.