User Manual 4.6 Optimization

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Révision de 12 janvier 2021 à 14:38 par Admin (discussion | contributions) (Features Description)

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Introduction

Scope

This section describes PATRIUS optimization features. It provides solvers for general convex optimization problems, such as LP, QP, QCQP, etc.

Javadoc

The math framework classes are available in the package fr.cnes.sirius.patrius.math.optim.

Library Javadoc
Patrius Package fr.cnes.sirius.patrius.math.optim

Links

None as of now.

Useful Documents

None as of now.

Package Overview

TODO

Features Description

Optimizers

The JOptimizer class implements the convex optimizer (see "S.Boyd and L.Vandenberghe, Convex Optimization").

The algorithm selection is implemented as a Chain of Responsibility pattern, and this class is the client of the chain.

The different methods implemented to solve the convex optimization problem are:

  • Interior point methods
    • PrimalDualMethod : primal-dual interior-point method.
    • LPPrimalDualMethod : primal-dual interior-point method for linear problems.
    • BarrierMethod
  • Quality constrained minimization
    • NewtonLEConstrainedFSP : linear equality constrained newton optimizer, with feasible starting point.
    • NewtonLEConstrainedISP : linear equality constrained newton optimizer, with infeasible starting point.
  • Unconstrained minimization
    • NewtonUnconstrained : unconstrained newton optimizer.

Optimization problem

The OptimizationRequest class has all the settting field's necessaires to define an optimization problem.

The LPOptimizationRequest is an extension of this class for linear optimization problems.

The general form of a linear problem is (1):

min(c) s.t.
A.x = b
lb <= x <= ub

The OptimizationResponse is the class with the getters and setters to set and get the response after the optimization. The LPOptimizationResponse is the extension class applied to linear problems.

Standard converter

The LPStandardConverter converts a general linear problem stated in the form (2):

min(c) s.t. 
G.x < h 
A.x = b 
lb <= x <= ub

to the (strictly)standard form:

min(c) s.t. 
A.x = b 
x >= 0

or to the (quasi)standard form (1).

Presolver

The LPPresolver implements a presolver for a linear problem in the form (1).

It applies a set of techniques on the linear programming problem before a linear programming solver solves it. This set of techniques aim at reducing the size of the LP problem by eliminating redundant constraints and variables and identifying possible infeasibility and unboundedness of the problem.

Solvers

The AbstractKKTSolver implements a solver for the KKT system:

H.v + [A]T.w = -g
A.v = -h

where H is a square and symmetric matrix.

The following classes are an extension of AbstractKKTSolver:

  • AugmentedKKTSolver (for singular H)
  • BasicKKTSolver
  • UpperDiagonalHKKTSolver (for upper diagonal H)

Functions

Different functions are implemented, all of them twice differentiable.

  • Linear functions

The LinearMultivariateRealFunction represents a function in the form of:

f(x) = q.x + r
  • Quadratic functions

The QuadraticMultivariateRealFunction represents a function in the form of:

f(x) := 1/2 x.P.x + q.x + r

where x, q ∈ R n, P is a symmetric nXn matrix and r ∈ R.

With an extension in PSDQuadraticMultivariateRealFunction and PDQuadraticMultivariateRealFunction for P symmetric and positive semi-definite, and P symmetric and positive definite,respectively.

  • Barrier functions

The LogarithmicBarrier is the default barrier function for the barrier method algorithm.

If fi(x) are the inequalities of the problem, then the function:

Φ(x) = − ∑_i (log(−fi(x)))

Algebra

Factorization

The CholeskyFactorization implements the Cholesky L.L[T] factorization and inverse for symmetric and positive matrix:

Q = L.L[T]

with L lower-triangular.

Getting Started

TODO

Contents

Interfaces

The most relevant interfaces related to the optimization are listed here :

Interface Summary Javadoc
BarrierFunction Interface for the barrier function used by a given barrier optimization method. ...
ConvexMultivariateRealFunction Interface for convex multivariate real functions. ...
MatrixRescaler An interface to classes that implement an algorithm to rescale matrices. ...
StrictlyConvexMultivariateRealFunction Interface for striclty convex multivariate real functions. ...
TwiceDifferentiableMultivariateRealFunction Interface for twice-differentiable multivariate functions. ...

Classes

The most relevant classes related to the optimization are listed here :

Class Summary Javadoc
AbstractKKTSolver Abstract class for solving KKT systems. ...
AbstractLPOptimizationRequestHandler Abstract class for Linear Problem Optimization Request Handler. ...
BarrierMethod Implements the Barrier Method. ...
BasicPhaseIBM Implements the Basic Phase I Method as a Barried Method. ...
BasicPhaseILPPDM Implements the Basic Phase I Method form LP problems as a Primal-Dual Method. ...
BasicPhaseIPDM Implements the Basic Phase I Method as a Primal-Dual Method. ...
CholeskyFactorization Implements the Cholesky L.L[T] factorization and inverse for symmetric and positive matrix. ...
JOptimizer Implements the convex optimizer. ...
LinearMultivariateRealFunction Defines a linear multivariate function in the form f(x) = q.x + r. ...
LogarithmicBarrier Default barrier function for the barrier method algorithm. ...
LPOptimizationRequest Implements a linear optimization problem. ...
LPOptimizationResponse Response of the linear optimization problem. ...
LPPresolver Presolver for a linear problem. ...
LPPrimalDualMethod Implements the Primal-dual interior-point method for linear problems. ...
LPStandardConverter Converts a general LP problem into a strictly standard or quasi standard form. ...
Matrix1NornRescaler Calculates the matrix rescaling factors so that the 1-norm of each row and each column of the scaled matrix asymptotically converges to one. ...
NewtonLEConstrainedFSP Linear equality constrained newton optimizer, with feasible starting point. ...
NewtonLEConstrainedISP Linear equality constrained newton optimizer, with infeasible starting point. ...
NewtonUnconstrained Unconstrained newton optimizer. ...
OptimizationRequest Implements an optimization problem. ...
OptimizationRequestHandler Generic class for optimization process. ...
OptimizationResponse Optimization process output: stores the solution as well as an exit code. ...
PrimalDualMethod Implements a primal-dual interior-point method. ...
QuadraticMultivariateRealFunction Implements a quadratic multivariate function in the form of f(x):= 1/2 x.P.x + q.x + r. ...