This repository has been archived by the owner on Nov 17, 2023. It is now read-only.
forked from rte-france/or-tools
-
Notifications
You must be signed in to change notification settings - Fork 0
/
update_row.h
161 lines (133 loc) · 6.25 KB
/
update_row.h
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
// Copyright 2010-2018 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifndef OR_TOOLS_GLOP_UPDATE_ROW_H_
#define OR_TOOLS_GLOP_UPDATE_ROW_H_
#include "ortools/glop/basis_representation.h"
#include "ortools/glop/parameters.pb.h"
#include "ortools/glop/variables_info.h"
#include "ortools/lp_data/lp_types.h"
#include "ortools/util/stats.h"
namespace operations_research {
namespace glop {
// During a simplex iteration, when the basis 'leaving_row' has been
// selected, one of the main quantities needed in the primal or dual simplex
// algorithm is called the update row.
//
// By definition, update_row[col] is the coefficient at position
// 'leaving_row' in the current basis of the column 'col' of the matrix A.
//
// One efficient way to compute it is to compute the left inverse by B of the
// unit vector with a one at the given leaving_row, and then to take the
// scalar product of this left inverse with all the columns of A:
// update_row[col] = (unit_{leaving_row} . B^{-1}) . A_col
class UpdateRow {
public:
// Takes references to the linear program data we need.
UpdateRow(const CompactSparseMatrix& matrix,
const CompactSparseMatrix& transposed_matrix,
const VariablesInfo& variables_info, const RowToColMapping& basis,
const BasisFactorization& basis_factorization);
// Invalidates the current update row and unit_row_left_inverse so the next
// call to ComputeUpdateRow() will recompute everything and not just return
// right away.
void Invalidate();
// Computes the relevant coefficients (See GetIsRelevantBitRow() in
// VariablesInfo) of the update row. The result is only computed once until
// the next Invalidate() call and calling this function more than once will
// have no effect until then.
void ComputeUpdateRow(RowIndex leaving_row);
// Returns the left inverse of the unit row as computed by the last call to
// ComputeUpdateRow(). In debug mode, we check that ComputeUpdateRow() was
// called since the last Invalidate().
const ScatteredRow& GetUnitRowLeftInverse() const;
// Returns the update coefficients and non-zero positions corresponding to the
// last call to ComputeUpdateRow().
const DenseRow& GetCoefficients() const;
const ColIndexVector& GetNonZeroPositions() const;
const Fractional GetCoefficient(ColIndex col) const {
return coefficient_[col];
}
// This must be called after a call to ComputeUpdateRow(). It will fill
// all the non-relevant positions that where not filled by ComputeUpdateRow().
void RecomputeFullUpdateRow(RowIndex leaving_row);
// Sets to zero the coefficient for column col.
void IgnoreUpdatePosition(ColIndex col);
// Sets the algorithm parameters.
void SetParameters(const GlopParameters& parameters);
// Returns statistics about this class as a std::string.
std::string StatString() const { return stats_.StatString(); }
// Only used for testing.
// Computes as the update row the product 'lhs' times the linear program
// matrix given at construction. Only the relevant columns matter (see
// VariablesInfo) and 'algorithm' can be one of "column", "row" or
// "row_hypersparse".
void ComputeUpdateRowForBenchmark(const DenseRow& lhs,
const std::string& algorithm);
// Deterministic time used by the scalar product computation of this class.
double DeterministicTime() const {
return DeterministicTimeForFpOperations(num_operations_);
}
// This returns the asked unit row left inverse. It temporarily invalidate
// the class state by calling Invalidate().
const ScatteredRow& ComputeAndGetUnitRowLeftInverse(RowIndex leaving_row);
private:
// Computes the left inverse of the given unit row, and stores it in
// unit_row_left_inverse_.
void ComputeUnitRowLeftInverse(RowIndex leaving_row);
// ComputeUpdateRow() does the common work and call one of these functions
// depending on the situation.
void ComputeUpdatesRowWise();
void ComputeUpdatesRowWiseHypersparse();
void ComputeUpdatesColumnWise();
// Problem data that should be updated from outside.
const CompactSparseMatrix& matrix_;
const CompactSparseMatrix& transposed_matrix_;
const VariablesInfo& variables_info_;
const RowToColMapping& basis_;
const BasisFactorization& basis_factorization_;
// Left inverse by B of a unit row. Its scalar product with a column 'a' of A
// gives the value of the right inverse of 'a' on the 'leaving_row'.
ScatteredRow unit_row_left_inverse_;
// The non-zeros of unit_row_left_inverse_ above the drop tolerance.
std::vector<ColIndex> unit_row_left_inverse_filtered_non_zeros_;
// Holds the current update row data.
// TODO(user): Introduce a ScatteredSparseRow class?
ColIndexVector non_zero_position_list_;
DenseBitRow non_zero_position_set_;
DenseRow coefficient_;
// Boolean used to avoid recomputing many times the same thing.
bool compute_update_row_;
RowIndex update_row_computed_for_;
// Statistics about this class.
struct Stats : public StatsGroup {
Stats()
: StatsGroup("UpdateRow"),
unit_row_left_inverse_density("unit_row_left_inverse_density", this),
unit_row_left_inverse_accuracy("unit_row_left_inverse_accuracy",
this),
update_row_density("update_row_density", this) {}
RatioDistribution unit_row_left_inverse_density;
DoubleDistribution unit_row_left_inverse_accuracy;
RatioDistribution update_row_density;
};
// Track the number of basic floating point multiplication.
// Used by DeterministicTime().
int64 num_operations_;
// Glop standard classes.
GlopParameters parameters_;
Stats stats_;
DISALLOW_COPY_AND_ASSIGN(UpdateRow);
};
} // namespace glop
} // namespace operations_research
#endif // OR_TOOLS_GLOP_UPDATE_ROW_H_