Clp 1.17.5
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ClpSimplexNonlinear.hpp
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1/* $Id: ClpSimplexNonlinear.hpp 2385 2019-01-06 19:43:06Z unxusr $ */
2// Copyright (C) 2004, International Business Machines
3// Corporation and others. All Rights Reserved.
4// This code is licensed under the terms of the Eclipse Public License (EPL).
5/*
6 Authors
7
8 John Forrest
9
10 */
11#ifndef ClpSimplexNonlinear_H
12#define ClpSimplexNonlinear_H
13
14class ClpNonlinearInfo;
16class ClpConstraint;
17
18#include "ClpSimplexPrimal.hpp"
19
29
30public:
38 int primal();
43 int primalSLP(int numberPasses, double deltaTolerance,
44 int otherOptions = 0);
46 int primalDualCuts(char *rowsIn, int startUp, int algorithm);
52 int primalSLP(int numberConstraints, ClpConstraint **constraints,
53 int numberPasses, double deltaTolerance);
54
60 void directionVector(CoinIndexedVector *longArray,
61 CoinIndexedVector *spare1, CoinIndexedVector *spare2,
62 int mode,
63 double &normFlagged, double &normUnflagged,
64 int &numberNonBasic);
66 int whileIterating(int &pivotMode);
79 int pivotColumn(CoinIndexedVector *longArray,
80 CoinIndexedVector *rowArray,
81 CoinIndexedVector *columnArray,
82 CoinIndexedVector *spare,
83 int &pivotMode,
84 double &solutionError,
85 double *array1);
95 void statusOfProblemInPrimal(int &lastCleaned, int type,
97 bool doFactorization,
98 double &bestObjectiveWhenFlagged);
113};
114#endif
115
116/* vi: softtabstop=2 shiftwidth=2 expandtab tabstop=2
117*/
Constraint Abstract Base Class.
Quadratic Objective Class.
This solves non-linear LPs using the primal simplex method.
void statusOfProblemInPrimal(int &lastCleaned, int type, ClpSimplexProgress *progress, bool doFactorization, double &bestObjectiveWhenFlagged)
Refactorizes if necessary Checks if finished.
int primalDualCuts(char *rowsIn, int startUp, int algorithm)
May use a cut approach for solving any LP.
int primalSLP(int numberPasses, double deltaTolerance, int otherOptions=0)
Primal algorithm for quadratic Using a semi-trust region approach as for pooling problem This is in b...
int pivotColumn(CoinIndexedVector *longArray, CoinIndexedVector *rowArray, CoinIndexedVector *columnArray, CoinIndexedVector *spare, int &pivotMode, double &solutionError, double *array1)
longArray has direction pivotMode - 0 - use all dual infeasible variables 1 - largest dj while >= 10 ...
int primal()
Primal algorithms for reduced gradient At present we have two algorithms:
int whileIterating(int &pivotMode)
Main part.
int pivotNonlinearResult()
Do last half of an iteration.
void directionVector(CoinIndexedVector *longArray, CoinIndexedVector *spare1, CoinIndexedVector *spare2, int mode, double &normFlagged, double &normUnflagged, int &numberNonBasic)
Creates direction vector.
int primalSLP(int numberConstraints, ClpConstraint **constraints, int numberPasses, double deltaTolerance)
Primal algorithm for nonlinear constraints Using a semi-trust region approach as for pooling problem ...
This solves LPs using the primal simplex method.
For saving extra information to see if looping.
Definition ClpSolve.hpp:310
int algorithm() const
Current (or last) algorithm.
CoinIndexedVector * rowArray(int index) const
Useful row length arrays (0,1,2,3,4,5)
CoinIndexedVector * columnArray(int index) const
Useful column length arrays (0,1,2,3,4,5)
ClpSimplexProgress * progress()
For dealing with all issues of cycling etc.