logo资料库

Engineering Optimization: Theory and Practice 4th.pdf

发布时间：2022-05-30 发布人：admin 分类：说明书 资料大小：11.03M 资料格式：pdf 举报 版权申诉
第1页 / 共829页
第2页 / 共829页
第3页 / 共829页
第4页 / 共829页
第5页 / 共829页
第6页 / 共829页
第7页 / 共829页
第8页 / 共829页
资料共829页，剩余部分请下载后查看
    Engineering Optimization.pdf
    1-Introduction to Optimization.pdf
    2-Classical Optimization Techniques.pdf
    3-Linear Programming I Simplex Method.pdf
    4-Linear Programming II Additional Topics and Extensions.pdf
    5-Nonlinear Programming I One-Dimensional Minimization Methods.pdf
    6-Nonlinear Programming II Unconstrained Optimization Techniques.pdf
    7-Nonlinear Programming III Constrained Optimization Techniques.pdf
    8-Geometric Programming.pdf
    9-Dynamic Programming.pdf
    10-Integer Programming.pdf
    11-Stochastic Programming.pdf
    12-Optimal Control and Optimality Criteria Methods.pdf
    13-Modern Methods of Optimization.pdf
    14-Practical Aspects of Optimization.pdf
    A-Convex and Concave Functions.pdf
    B-Some Computational Aspects of Optimization.pdf
    C- Introduction to MATLAB®.pdf
    Answers to Selected Problems.pdf
    Index.pdf
    Engineering Optimization Engineering Optimization: Theory and Practice, Fourth Edition Copyright © 2009 by John Wiley & Sons, Inc. Singiresu S. Rao
    Engineering Optimization Theory and Practice Fourth Edition Singiresu S. Rao JOHN WILEY & SONS, INC.
    This book is printed on acid-free paper. Copyright c 2009 by John Wiley & Sons, Inc. All rights reserved Published by John Wiley & Sons, Inc., Hoboken, New Jersey Published simultaneously in Canada No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording, scanning, or otherwise, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without either the prior written permission of the Publisher, or authorization through payment of the appropriate per-copy fee to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923, (978) 750– 8400, fax (978) 646– 8600, or on the web at www.copyright.com. Requests to the Publisher for permission should be addressed to the Permissions Department, John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030, (201) 748– 6011, fax (201) 748– 6008, or online at www.wiley.com/go/permissions. Limit of Liability/Disclaimer of Warranty: While the publisher and the author have used their best efforts in preparing this book, they make no representations or warranties with respect to the accuracy or completeness of the contents of this book and specifically disclaim any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives or written sales materials. The advice and strategies contained herein may not be suitable for your situation. You should consult with a professional where appropriate. Neither the publisher nor the author shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages. For general information about our other products and services, please contact our Customer Care Department within the United States at (800) 762– 2974, outside the United States at (317) 572– 3993 or fax (317) 572– 4002. Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available in electronic books. For more information about Wiley products, visit our web site at www.wiley.com. Library of Congress Cataloging-in-Publication Data: Rao, S. S. Engineering optimization : theory and practice / Singiresu S. Rao.– 4th ed. p. cm. Includes index. ISBN 978-0-470-18352-6 (cloth) 1. Engineering— Mathematical models. 2. Mathematical optimization. I. Title. TA342.R36 2009 620.001′5196— dc22 Printed in the United States of America 10 9 8 7 6 5 4 3 2 1 2009018559
    Contents Preface xvii 1 Introduction to Optimization 1 1.1 1.2 1.3 1.4 Introduction 1 Historical Development 3 Engineering Applications of Optimization 5 Statement of an Optimization Problem 6 1.4.1 Design Vector 6 1.4.2 Design Constraints 1.4.3 Constraint Surface 1.4.4 Objective Function 7 8 9 1.4.5 Objective Function Surfaces 9 1.5 Classification of Optimization Problems 14 1.5.1 Classification Based on the Existence of Constraints 14 1.5.2 Classification Based on the Nature of the Design Variables 15 1.5.3 Classification Based on the Physical Structure of the Problem 1.5.4 Classification Based on the Nature of the Equations Involved 16 19 1.5.5 Classification Based on the Permissible Values of the Design Variables 28 1.5.6 Classification Based on the Deterministic Nature of the Variables 29 1.5.7 Classification Based on the Separability of the Functions 30 1.5.8 Classification Based on the Number of Objective Functions 32 1.6 1.7 1.8 Optimization Techniques 35 Engineering Optimization Literature 35 Solution of Optimization Problems Using MATLAB 36 References and Bibliography 39 Review Questions 45 Problems 46 2 Classical Optimization Techniques 63 2.1 2.2 Introduction 63 Single-Variable Optimization 63 2.3 Multivariable Optimization with No Constraints 68 2.3.1 2.3.2 Semidefinite Case 73 Saddle Point 73 2.4 Multivariable Optimization with Equality Constraints 75 2.4.1 2.4.2 2.4.3 Solution by Direct Substitution 76 Solution by the Method of Constrained Variation Solution by the Method of Lagrange Multipliers 77 85 vii
    viii Contents 2.5 Multivariable Optimization with Inequality Constraints 93 2.5.1 Kuhn – Tucker Conditions 98 2.5.2 Constraint Qualification 98 2.6 Convex Programming Problem 104 References and Bibliography 105 Review Questions 105 Problems 106 3 Linear Programming I: Simplex Method 119 3.1 3.2 3.3 3.4 3.5 3.6 3.7 Introduction 119 Applications of Linear Programming 120 Standard Form of a Linear Programming Problem 122 Geometry of Linear Programming Problems 124 Definitions and Theorems 127 Solution of a System of Linear Simultaneous Equations 133 Pivotal Reduction of a General System of Equations 135 3.8 Motivation of the Simplex Method 138 3.9 Simplex Algorithm 139 3.9.1 3.9.2 Identifying an Optimal Point 140 Improving a Nonoptimal Basic Feasible Solution 141 3.10 Two Phases of the Simplex Method 3.11 MATLAB Solution of LP Problems 150 156 References and Bibliography 158 Review Questions 158 Problems 160 4 Linear Programming II: Additional Topics and Extensions 177 4.1 4.2 4.3 4.4 4.5 Introduction 177 Revised Simplex Method 177 Duality in Linear Programming 192 4.3.1 Symmetric Primal – Dual Relations 192 4.3.2 General Primal – Dual Relations 193 4.3.3 Primal – Dual Relations When the Primal Is in Standard Form 193 4.3.4 Duality Theorems 195 4.3.5 Dual Simplex Method 195 Decomposition Principle 200 Sensitivity or Postoptimality Analysis 4.5.1 Changes in the Right-Hand-Side Constants bi 4.5.2 Changes in the Cost Coefficients cj 4.5.3 Addition of New Variables 214 4.5.4 Changes in the Constraint Coefficients aij 4.5.5 Addition of Constraints 212 207 218 208 215 4.6 Transportation Problem 220
    4.7 Karmarkar’s Interior Method 222 4.7.1 Statement of the Problem 223 4.7.2 Conversion of an LP Problem into the Required Form 224 Contents ix 4.7.3 Algorithm 226 4.8 Quadratic Programming 229 4.9 MATLAB Solutions 235 References and Bibliography 237 Review Questions 239 Problems 239 5 Nonlinear Programming I: One-Dimensional Minimization Methods 248 5.1 5.2 Introduction 248 Unimodal Function 253 ELIMINATION METHODS 254 5.3 Unrestricted Search 254 5.3.1 Search with Fixed Step Size 254 5.3.2 Search with Accelerated Step Size 255 5.4 5.5 5.6 5.7 5.8 5.9 Exhaustive Search 256 Dichotomous Search 257 Interval Halving Method 260 Fibonacci Method 263 Golden Section Method 267 Comparison of Elimination Methods 271 INTERPOLATION METHODS 271 5.10 Quadratic Interpolation Method 273 5.11 Cubic Interpolation Method 280 5.12 Direct Root Methods 286 5.12.1 Newton Method 286 5.12.2 Quasi-Newton Method 288 5.12.3 Secant Method 5.13 Practical Considerations 290 293 5.13.1 How to Make the Methods Efficient and More Reliable 5.13.2 Implementation in Multivariable Optimization Problems 293 293 5.13.3 Comparison of Methods 294 5.14 MATLAB Solution of One-Dimensional Minimization Problems 294 References and Bibliography 295 Review Questions 295 Problems 296
    x Contents 6 Nonlinear Programming II: Unconstrained Optimization Techniques 301 6.1 Introduction 301 6.1.1 Classification of Unconstrained Minimization Methods 304 6.1.2 General Approach 305 6.1.3 Rate of Convergence 305 6.1.4 Scaling of Design Variables 305 DIRECT SEARCH METHODS 309 6.2 Random Search Methods 309 6.2.1 Random Jumping Method 311 6.2.2 Random Walk Method 312 6.2.3 Random Walk Method with Direction Exploitation 313 6.2.4 Advantages of Random Search Methods 314 6.3 6.4 6.5 6.6 Grid Search Method 314 Univariate Method Pattern Directions 315 318 Powell’s Method 319 6.6.1 Conjugate Directions 319 6.6.2 Algorithm 323 6.7 Simplex Method 328 6.7.1 Reflection 6.7.2 Expansion 328 331 6.7.3 Contraction 332 INDIRECT SEARCH (DESCENT) METHODS 335 6.8 Gradient of a Function 335 6.8.1 Evaluation of the Gradient 337 6.8.2 Rate of Change of a Function along a Direction 338 6.9 Steepest Descent (Cauchy) Method 339 6.10 Conjugate Gradient (Fletcher– Reeves) Method 341 6.10.1 Development of the Fletcher– Reeves Method 342 6.10.2 Fletcher– Reeves Method 343 6.11 Newton’s Method 6.12 Marquardt Method 345 348 6.13 Quasi-Newton Methods 350 6.13.1 Rank 1 Updates 6.13.2 Rank 2 Updates 351 352 6.14 Davidon – Fletcher– Powell Method 354 6.15 Broyden – Fletcher– Goldfarb – Shanno Method 360 6.16 Test Functions 363 6.17 MATLAB Solution of Unconstrained Optimization Problems 365 References and Bibliography 366 Review Questions 368 Problems 370
    分享到：
    赞 收藏

    相关推荐

    资料库

    开发技术

    共收录19306份资料，累计14个分类，关注成员有19位，主要包括：Actionscript,Javascript,PHP,VB,Perl,Delphi,Python,C#,C,Java,C++,Web开发,硬件开发,其它

    热门标签

    Actionscript Javascript PHP VB Perl Delphi Python C# C Java C++ Web开发 硬件开发 其它

    最新资料