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Sequential Quadratic Programming
Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization, also known as Lagrange-Newton method. SQP methods are used on mathematical problems for which the objective function and the constraints are twice continuously differentiable, but not necessarily convex. SQP methods solve a sequence of optimization subproblems, each of which optimizes a quadratic model of the objective subject to a linearization of the constraints. If the problem is unconstrained, then the method reduces to Newton's method for finding a point where the gradient of the objective vanishes. If the problem has only equality constraints, then the method is equivalent to applying Newton's method to the first-order optimality conditions, or Karush–Kuhn–Tucker conditions, of the problem. Algorithm basics Consider a nonlinear programming problem of the form: :\begin \min\limits_ & f(x) \\ \mbox & h(x) \ge 0 \\ & g(x) = 0. \end where x \in \mathbb^n, f: \mathbb ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Iterative Method
In computational mathematics, an iterative method is a Algorithm, mathematical procedure that uses an initial value to generate a sequence of improving approximate solutions for a class of problems, in which the ''i''-th approximation (called an "iterate") is derived from the previous ones. A specific implementation with Algorithm#Termination, termination criteria for a given iterative method like gradient descent, hill climbing, Newton's method, or Quasi-Newton method, quasi-Newton methods like Broyden–Fletcher–Goldfarb–Shanno algorithm, BFGS, is an algorithm of an iterative method or a method of successive approximation. An iterative method is called ''Convergent series, convergent'' if the corresponding sequence converges for given initial approximations. A mathematically rigorous convergence analysis of an iterative method is usually performed; however, heuristic-based iterative methods are also common. In contrast, direct methods attempt to solve the problem by a finit ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Sequential Linear-quadratic Programming
Sequential linear-quadratic programming (SLQP) is an iterative method for nonlinear optimization problems where objective function and constraints are twice continuously differentiable. Similarly to sequential quadratic programming (SQP), SLQP proceeds by solving a sequence of optimization subproblems. The difference between the two approaches is that: * in SQP, each subproblem is a quadratic program, with a quadratic model of the objective subject to a linearization of the constraints * in SLQP, two subproblems are solved at each step: a linear program (LP) used to determine an active set, followed by an equality-constrained quadratic program (EQP) used to compute the total step This decomposition makes SLQP suitable to large-scale optimization problems, for which efficient LP and EQP solvers are available, these problems being easier to scale than full-fledged quadratic programs. It may be considered related to, but distinct from, quasi-Newton methods. Algorithm basics Con ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SuanShu Numerical Library
SuanShu is a Java (programming language), Java math library. It is open-source under Apache License 2.0 available iGitHub SuanShu is a large collection of Java classes for basic numerical analysis, statistics, and optimization. It implements a parallel version of the adaptive strassen's algorithm for fast matrix multiplication. SuanShu has been quoted and used in a number of academic works. Features * linear algebra * root finding * curve fitting and interpolation * unconstrained and constrained optimization * statistical analysis * linear regression * probability distributions and random number generation * ordinary and partial differential equation solvers License terms SuanShu is released under the terms of the Apache License 2.0 Examples of usage The following code shows the object-oriented design of the library (in contrast to the traditional procedural design of many other Numerical Recipes, FORTRAN and C numerical libraries) by a simple example of minimization. Lo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NLPQL
The Fortran subroutine ''NLPQLP'', a newer version of ''NLPQL'', solves smooth nonlinear programming problems by a sequential quadratic programming Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization, also known as Lagrange-Newton method. SQP methods are used on mathematical problems for which the objective function and the constraints are twi ... (SQP) algorithm. The new version is specifically tuned to run under distributed systems. In case of computational errors, such as inaccurate function or gradient evaluations, a non-monotone line search is activated. The code is easily transformed to C by f2c and is widely used in academia and industry. References * External links * http://klaus-schittkowski.de/nlpqlp.htm * https://www.schittkowski.de/numericalsoftware_nlpqlp.php Mathematical software {{Compu-library-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SNOPT
SNOPT, for Sparse Nonlinear OPTimizer, is a software package for solving large-scale nonlinear optimization problems written by Philip Gill, Walter Murray and Michael Saunders. SNOPT is mainly written in Fortran, but interfaces to C, C++, Python and MATLAB are available. It employs a sparse sequential quadratic programming (SQP) algorithm with limited-memory quasi-Newton approximations to the Hessian of the Lagrangian. It is especially effective for nonlinear problems with functions and gradients that are expensive to evaluate. The functions should be smooth but need not be convex. SNOPT is used in several trajectory optimization software packages, including Copernicus, AeroSpace Trajectory Optimization and Software ( ASTOS), General Mission Analysis Tool, and Optimal Trajectories by Implicit Simulation (OTIS). It is also available in the Astrogator module of Systems Tool Kit. SNOPT is supported in the AIMMS, AMPL AMPL (A Mathematical Programming Language) is an al ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
NPSOL
NPSOL is a software package that performs numerical optimization. It solves nonlinear constrained problems using the sequential quadratic programming algorithm. It was written in Fortran by Philip Gill of UCSD and Walter Murray, Michael Saunders and Margaret Wright of Stanford University Leland Stanford Junior University, commonly referred to as Stanford University, is a Private university, private research university in Stanford, California, United States. It was founded in 1885 by railroad magnate Leland Stanford (the eighth .... The name derives from a combination of NP for nonlinear programming and SOL, the Systems Optimization Laboratory at Stanford. References {{Citation , last = Gill , first = Philip , last2 = Murray , first2 = Walter , last3 = Saunders , first3 = Michael , last4 = Wright , first4 = Margaret , title = User's Guide for NPSOL 5.0: A Fortran Package for Nonlinear Programming , work = Technical Report SOL 86-6 , date = 4 J ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
KNITRO
Artelys Knitro is a commercial software package for solving large scale nonlinear mathematical optimization problems. KNITRO – (the original solver name) short for "Nonlinear Interior point Trust Region Optimization" (the "K" is silent) – was co-created by Richard Waltz, Jorge Nocedal, Todd Plantenga and Rich Byrd. It was first introduced in 2001, as a derivative of academic research at Northwestern University. Subsequently, it was developed by Ziena Optimization LLC, which has been bought by Frech Artelys. Optimization problems must be presented to Knitro in mathematical form, and should provide a way of computing function derivatives using sparse matrices (Knitro can compute derivatives approximation but in most cases providing the exact derivatives is beneficial). An often easier approach is to develop the optimization problem in an algebraic modeling language. The modeling environment computes function derivatives, and Knitro is called as a "solver" from within the e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Optimal Control
Optimal control theory is a branch of control theory that deals with finding a control for a dynamical system over a period of time such that an objective function is optimized. It has numerous applications in science, engineering and operations research. For example, the dynamical system might be a spacecraft with controls corresponding to rocket thrusters, and the objective might be to reach the Moon with minimum fuel expenditure. Or the dynamical system could be a nation's economy, with the objective to minimize unemployment; the controls in this case could be fiscal and monetary policy. A dynamical system may also be introduced to embed operations research problems within the framework of optimal control theory. Optimal control is an extension of the calculus of variations, and is a mathematical optimization method for deriving control policies. The method is largely due to the work of Lev Pontryagin and Richard Bellman in the 1950s, after contributions to calculus of v ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ALGLIB
ALGLIB is a cross-platform open source numerical analysis and data processing library. It can be used from several programming languages ( C++, C#, VB.NET, Python, Delphi, Java). ALGLIB started in 1999 and has a long history of steady development with roughly 1-3 releases per year. It is used by several open-source projects, commercial libraries, and applications (e.g. TOL project, Math.NET Numerics, SpaceClaim). Features Distinctive features of the library are: * Support for several programming languages with identical APIs (as of 2023, it supports C++, C#, FreePascal/Delphi, VB.NET, Python, and Java) * Self-contained code with no mandatory external dependencies and easy installation * Portability (it was tested under x86/x86-64/ARM, Windows and Linux) * Two independent backends (pure C# implementation, native C implementation) with automatically generated APIs (C++, C#, ...) * Same functionality of commercial and GPL versions, with enhancements for speed and parallelism ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
SciPy
SciPy (pronounced "sigh pie") is a free and open-source Python library used for scientific computing and technical computing. SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, fast Fourier transform, signal and image processing, ordinary differential equation solvers and other tasks common in science and engineering. SciPy is also a family of conferences for users and developers of these tools: SciPy (in the United States), EuroSciPy (in Europe) and SciPy.in (in India). Enthought originated the SciPy conference in the United States and continues to sponsor many of the international conferences as well as host the SciPy website. The SciPy library is currently distributed under the BSD license, and its development is sponsored and supported by an open community of developers. It is also supported by NumFOCUS, a community foundation for supporting reproducible and accessible science. Components The SciPy package is at the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
