Engineering Optimization Theory and Practice by Singiresu S. Rao

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Engineering Optimization Theory and Practice

PDF Free Download | Engineering Optimization Theory and Practice 4th Edition by Singiresu S. Rao

Contents of Engineering Optimization PDF

  • Introduction to Optimization
  • Historical Development
  • Engineering Applications of Optimization
  • Statement of an Optimization Problem
  • Design Vector
  • Design Constraints
  • Constraint Surface
  • Objective Function
  • Objective Function Surfaces
  • Classification of Optimization Problems
  • Classification Based on the Existence of Constraints
  • Classification Based on the Nature of the Design Variables
  • Classification Based on the Physical Structure of the Problem
  • Classification Based on the Nature of the Equations Involved
  • Classification Based on the Permissible Values of the Design Variables
  • Classification Based on the Deterministic Nature of the Variables
  • Classification Based on the Separability of the Functions
  • Classification Based on the Number of Objective Functions
  • Optimization Techniques
  • Engineering Optimization Literature
  • Solution of Optimization Problems Using MATLAB
  • Single-Variable Optimization
  • Multivariable Optimization with No Constraints
  • Semidefinite Case
  • Saddle Point
  • Multivariable Optimization with Equality Constraints
  • Solution by Direct Substitution
  • Solution by the Method of Constrained Variation
  • Solution by the Method of Lagrange Multipliers
  • Multivariable Optimization with Inequality Constraints
  • Kuhn–Tucker Conditions
  • Constraint Qualification
  • Convex Programming Problem
  • Linear Programming I: Simplex Method
  • Applications of Linear Programming
  • Standard Form of a Linear Programming Problem
  • Geometry of Linear Programming Problems
  • Definitions and Theorems
  • Solution of a System of Linear Simultaneous Equations
  • Pivotal Reduction of a General System of Equations
  • Motivation of the Simplex Method
  • Simplex Algorithm
  • Identifying an Optimal Point
  • Improving a Nonoptimal Basic Feasible Solution
  • Two Phases of the Simplex Method
  • MATLAB Solution of LP Problems
  • Linear Programming II: Additional Topics and Extensions
  • Revised Simplex Method
  • Duality in Linear Programming
  • Symmetric Primal–Dual Relations
  • General Primal–Dual Relations
  • Primal–Dual Relations When the Primal Is in Standard Form
  • Duality Theorems
  • Dual Simplex Method
  • Decomposition Principle
  • Sensitivity or Postoptimality Analysis
  • Changes in the Right-Hand-Side Constants bi
  • Changes in the Cost Coefficients cj
  • Addition of New Variables
  • Changes in the Constraint Coefficients aij
  • Addition of Constraints
  • Transportation Problem
  • Karmarkar’s Interior Method
  • Statement of the Problem
  • Conversion of an LP Problem into the Required Form
  • Algorithm
  • Quadratic Programming
  • MATLAB Solutions
  • Nonlinear Programming I: One-Dimensional Minimization Methods
  • Unimodal Function
  • ELIMINATION METHODS
  • Unrestricted Search
  • Search with Fixed Step Size
  • Search with Accelerated Step Size
  • Exhaustive Search
  • Dichotomous Search
  • Interval Halving Method
  • Fibonacci Method
  • Golden Section Method
  • Comparison of Elimination Methods
  • INTERPOLATION METHODS
  • Quadratic Interpolation Method
  • Cubic Interpolation Method
  • Direct Root Methods
  • Newton Method
  • Quasi-Newton Method
  • Secant Method
  • Practical Considerations
  • How to Make the Methods Efficient and More Reliable
  • Implementation in Multivariable Optimization Problems
  • Comparison of Methods
  • MATLAB Solution of One-Dimensional Minimization Problems
  • Nonlinear Programming II: Unconstrained Optimization Techniques
  • Classification of Unconstrained Minimization Methods
  • General Approach
  • Rate of Convergence
  • Scaling of Design Variables
  • DIRECT SEARCH METHODS
  • Random Search Methods
  • Random Jumping Method
  • Random Walk Method
  • Random Walk Method with Direction Exploitation
  • Advantages of Random Search Methods
  • Grid Search Method
  • Univariate Method
  • Pattern Directions
  • Powell’s Method
  • Conjugate Directions
  • Algorithm
  • Simplex Method
  • Reflection
  • Expansion
  • Contraction
  • INDIRECT SEARCH (DESCENT) METHODS
  • Gradient of a Function
  • Evaluation of the Gradient
  • Rate of Change of a Function along a Direction
  • Steepest Descent (Cauchy) Method
  • Conjugate Gradient (Fletcher–Reeves) Method
  • Development of the Fletcher–Reeves Method
  • Fletcher–Reeves Method
  • Newton’s Method
  • Marquardt Method
  • Quasi-Newton Methods
  • Rank Updates
  • Rank Updates
  • Davidon–Fletcher–Powell Method
  • Broyden–Fletcher–Goldfarb–Shanno Method
  • Test Functions
  • MATLAB Solution of Unconstrained Optimization Problems
  • Nonlinear Programming III: Constrained Optimization Techniques
  • Characteristics of a Constrained Problem
  • DIRECT METHODS
  • Random Search Methods
  • Complex Method
  • Sequential Linear Programming
  • Basic Approach in the Methods of Feasible Directions
  • Zoutendijk’s Method of Feasible Directions
  • Direction-Finding Problem
  • Determination of Step Length
  • Termination Criteria
  • Rosen’s Gradient Projection Method
  • Determination of Step Length
  • Generalized Reduced Gradient Method
  • Sequential Quadratic Programming
  • Derivation
  • Solution Procedure
  • INDIRECT METHODS
  • Transformation Techniques
  • Basic Approach of the Penalty Function Method
  • Interior Penalty Function Method
  • Convex Programming Problem
  • Exterior Penalty Function Method
  • Extrapolation Techniques in the Interior Penalty Function Method
  • Extrapolation of the Design Vector X
  • Extrapolation of the Function f
  • Extended Interior Penalty Function Methods
  • Linear Extended Penalty Function Method
  • Quadratic Extended Penalty Function Method
  • Penalty Function Method for Problems with Mixed Equality and Inequality
  • Constraints
  • Interior Penalty Function Method
  • Exterior Penalty Function Method
  • Penalty Function Method for Parametric Constraints
  • Parametric Constraint
  • Handling Parametric Constraints
  • Augmented Lagrange Multiplier Method
  • Equality-Constrained Problems
  • Inequality-Constrained Problems
  • Mixed Equality–Inequality-Constrained Problems
  • Checking the Convergence of Constrained Optimization Problems
  • Perturbing the Design Vector
  • Testing the Kuhn–Tucker Conditions
  • Test Problems
  • Design of a Three-Bar Truss
  • Design of a Twenty-Five-Bar Space Truss
  • Welded Beam Design
  • Speed Reducer (Gear Train) Design
  • Heat Exchanger Design
  • MATLAB Solution of Constrained Optimization Problems
  • Geometric Programming
  • Posynomial
  • Unconstrained Minimization Problem
  • Solution of an Unconstrained Geometric Programming Program Using Differential
  • Calculus
  • Solution of an Unconstrained Geometric Programming Problem Using
  • Arithmetic–Geometric Inequality
  • Primal–Dual Relationship and Sufficiency Conditions in the Unconstrained
  • Case
  • Constrained Minimization
  • Solution of a Constrained Geometric Programming Problem
  • Primal and Dual Programs in the Case of Less-Than Inequalities
  • Geometric Programming with Mixed Inequality Constraints
  • Complementary Geometric Programming
  • Applications of Geometric Programming
  • Dynamic Programming
  • Multistage Decision Processes
  • Definition and Examples
  • Representation of a Multistage Decision Process
  • Conversion of a Nonserial System to a Serial System
  • Types of Multistage Decision Problems
  • Concept of Suboptimization and Principle of Optimality
  • Computational Procedure in Dynamic Programming
  • Example Illustrating the Calculus Method of Solution
  • Example Illustrating the Tabular Method of Solution
  • Conversion of a Final Value Problem into an Initial Value Problem
  • Linear Programming as a Case of Dynamic Programming
  • Continuous Dynamic Programming
  • Additional Applications
  • Design of Continuous Beams
  • Optimal Layout (Geometry) of a Truss
  • Optimal Design of a Gear Train
  • Design of a Minimum-Cost Drainage System
  • Integer Programming
  • INTEGER LINEAR PROGRAMMING
  • Graphical Representation
  • Gomory’s Cutting Plane Method
  • Concept of a Cutting Plane
  • Gomory’s Method for All-Integer Programming Problems
  • Gomory’s Method for Mixed-Integer Programming Problems
  • Balas’ Algorithm for Zero–One Programming Problems
  • INTEGER NONLINEAR PROGRAMMING
  • Integer Polynomial Programming
  • Representation of an Integer Variable by an Equivalent System of Binary
  • Variables
  • Conversion of a Zero–One Polynomial Programming Problem into a
  • Zero–One LP Problem
  • Branch-and-Bound Method
  • Sequential Linear Discrete Programming
  • Generalized Penalty Function Method
  • Solution of Binary Programming Problems Using MATLAB
  • Stochastic Programming
  • Basic Concepts of Probability Theory
  • Definition of Probability
  • Random Variables and Probability Density Functions
  • Mean and Standard Deviation
  • Function of a Random Variable
  • Jointly Distributed Random Variables
  • Covariance and Correlation
  • Functions of Several Random Variables
  • Probability Distributions
  • Central Limit Theorem
  • Stochastic Linear Programming
  • Stochastic Nonlinear Programming
  • Objective Function
  • Constraints
  • Stochastic Geometric Programming
  • Optimal Control and Optimality Criteria Methods
  • Calculus of Variations
  • Problem of Calculus of Variations
  • Lagrange Multipliers and Constraints
  • Generalization
  • Optimal Control Theory
  • Necessary Conditions for Optimal Control
  • Necessary Conditions for a General Problem
  • Optimality Criteria Methods
  • Optimality Criteria with a Single Displacement Constraint
  • Optimality Criteria with Multiple Displacement Constraints
  • Reciprocal Approximations
  • Modern Methods of Optimization
  • Genetic Algorithms
  • Representation of Design Variables
  • Representation of Objective Function and Constraints
  • Genetic Operators
  • Algorithm
  • Numerical Results
  • Simulated Annealing
  • Procedure
  • Algorithm
  • Features of the Method
  • Numerical Results
  • Particle Swarm Optimization
  • Computational Implementation of PSO
  • Improvement to the Particle Swarm Optimization Method
  • Solution of the Constrained Optimization Problem
  • Ant Colony Optimization
  • Basic Concept
  • Ant Searching Behavior
  • Path Retracing and Pheromone Updating
  • Pheromone Trail Evaporation
  • Algorithm
  • Optimization of Fuzzy Systems
  • Fuzzy Set Theory
  • Optimization of Fuzzy Systems
  • Computational Procedure
  • Numerical Results
  • Neural-Network-Based Optimization
  • Practical Aspects of Optimization
  • Reduction of Size of an Optimization Problem
  • Reduced Basis Technique
  • Design Variable Linking Technique
  • Fast Reanalysis Techniques
  • Incremental Response Approach
  • Basis Vector Approach
  • Derivatives of Static Displacements and Stresses
  • Derivatives of Eigenvalues and Eigenvectors
  • Derivatives of λi
  • Derivatives of Yi
  • Derivatives of Transient Response
  • Sensitivity of Optimum Solution to Problem Parameters
  • Sensitivity Equations Using Kuhn–Tucker Conditions
  • Sensitivity Equations Using the Concept of Feasible Direction
  • Multilevel Optimization
  • Basic Idea
  • Method
  • Parallel Processing
  • Multiobjective Optimization
  • Utility Function Method
  • Inverted Utility Function Method
  • Global Criterion Method
  • Bounded Objective Function Method
  • Lexicographic Method
  • Goal Programming Method
  • Goal Attainment Method
  • Solution of Multiobjective Problems Using MATLAB

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All books on this website are published in good faith and for educational information purpose only. So, we ask you to report us any copyrighted material published in our website and we will remove it immediately.