Corpus ID: 59804368

Springer Series in Operations Research

@inproceedings{Nocedal1999SpringerSI,
  title={Springer Series in Operations Research},
  author={Jorge Nocedal and Stephen J. Wright},
  year={1999}
}
Real-time capable driving strategy for EVs using linear MPC
TLDR
A novel approach for computation of energy efficient speed trajectories for EVs utilizing lookahead data for the road provided by advanced navigational systems and a simplified vehicle model is presented. Expand
Descent line search scheme using Gers̆gorin circle theorem
TLDR
In this framework, a safeguard based on Gersgorin Circle’s theorem provides an approximation of the Hessian that improves with iteration count, and Convergence analysis of the scheme is validated by numerical experiments. Expand
An alternative method for constrained optimization
We introduce an alternative approach for constrained mathematical programming problems. It rests on two main aspects: an efficient way to compute optimal solutions for unconstrained problems, andExpand
A REVIEW OF LINE SEARCH SEQUENTIAL QUADRATIC PROGRAMMING AND IT IS RATE OF CONVERGENCE
In the last few years the sequential quadratic programming (SQP) methods proposed by Wilson and developed by Han and Powell have widely been  recognized as most effective methods for solvingExpand
A General Low Rank Update Based Quadratic Programming Solver
  • 2007
Agricultural data prediction by means of neural network
The contribution deals with the prediction of crop yield levels, using an artificial intelligence approach, namely a multi-layer neural network model. Subsequently, we are contrasting this approachExpand
Basin of Attraction as a measure of robustness of an optimization algorithm
  • Ken K. T. Tsang
  • Computer Science
  • 2018 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)
  • 2018
TLDR
Numerical examples of BOA for canned commercial optimizer: fmincon in MATLAB's toolbox (Sequential Quadratic Programming, sqp, and Interior-Point Algorithm) are given as illustrations of how BOA can be used as a tool to compare the robustness of optimization algorithms. Expand
Optimal control and numerical optimization for missile interception guidance
TLDR
A direct optimal control approach is deployed, based on multiple shooting and a sequential quadratic programming algorithm for solving the resulting nonlinear optimization problem, that illustrates the overall efficiency of numerical optimization as a guidance scheme. Expand
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References

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INEXACT NEWTON METHODS
A classical algorithm for solving the system of nonlinear equations $F(x) = 0$ is Newton’s method \[ x_{k + 1} = x_k + s_k ,\quad {\text{where }}F'(x_k )s_k = - F(x_k ),\quad x_0 {\text{ given}}.\]...
Practical optimization
TLDR
This ebook Practical Optimization by Philip E. Gill is presented in pdf format and the full version of this ebook in DjVu, ePub, doc, txt, PDF forms is presented. Expand
Introduction to linear and nonlinear programming
andC.M.Reeves,Functionminimization by conjugate gradients
  • Computer Journal,
  • 1964
More AD of Nonlinear AMPL Models: Computing Hessian Information and Exploiting Partial Separability†
We describe computational experience with automatic differentiation of mathematical programming problems expressed in the modeling language AMPL. Nonlinear expressions are translated to loop-freeExpand
The Mathematica Book
From the Publisher: Mathematica has defined the state of the art in technical computing for over a decade, and has become a standard in many of the world's leading companies and universities. FromExpand
and R
  • H. Byrd,A family of trust-region-based algorithms for unconstrained minimization with strong global convergence properties, SIAM Journal on Numerical Analysis, 22
  • 1985
Global Convergence Properties of Conjugate Gradient Methods for Optimization
This paper explores the convergence of nonlinear conjugate gradient methods without restarts, and with practical line searches. The analysis covers two classes of methods that are globally convergentExpand
Introduction to Numerical Analysis
1. The numerical evaluation of expressions 2. Linear systems of equations 3. Interpolation and numerical differentiation 4. Numerical integration 5. Univariate nonlinear equations 6. Systems ofExpand
An Interior Point Algorithm for Large-Scale Nonlinear Programming
The design and implementation of a new algorithm for solving large nonlinear programming problems is described. It follows a barrier approach that employs sequential quadratic programming and trustExpand
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