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39 | |
40 | #include "qsimplex_p.h" |
41 | |
42 | #include <QtCore/qset.h> |
43 | #include <QtCore/qdebug.h> |
44 | |
45 | #include <stdlib.h> |
46 | |
47 | QT_BEGIN_NAMESPACE |
48 | |
49 | /*! |
50 | \internal |
51 | \class QSimplex |
52 | |
53 | The QSimplex class is a Linear Programming problem solver based on the two-phase |
54 | simplex method. |
55 | |
56 | It takes a set of QSimplexConstraints as its restrictive constraints and an |
57 | additional QSimplexConstraint as its objective function. Then methods to maximize |
58 | and minimize the problem solution are provided. |
59 | |
60 | The two-phase simplex method is based on the following steps: |
61 | First phase: |
62 | 1.a) Modify the original, complex, and possibly not feasible problem, into a new, |
63 | easy to solve problem. |
64 | 1.b) Set as the objective of the new problem, a feasible solution for the original |
65 | complex problem. |
66 | 1.c) Run simplex to optimize the modified problem and check whether a solution for |
67 | the original problem exists. |
68 | |
69 | Second phase: |
70 | 2.a) Go back to the original problem with the feasibl (but not optimal) solution |
71 | found in the first phase. |
72 | 2.b) Set the original objective. |
73 | 3.c) Run simplex to optimize the original problem towards its optimal solution. |
74 | */ |
75 | |
76 | /*! |
77 | \internal |
78 | */ |
79 | QSimplex::QSimplex() : objective(nullptr), rows(0), columns(0), firstArtificial(0), matrix(nullptr) |
80 | { |
81 | } |
82 | |
83 | /*! |
84 | \internal |
85 | */ |
86 | QSimplex::~QSimplex() |
87 | { |
88 | clearDataStructures(); |
89 | } |
90 | |
91 | /*! |
92 | \internal |
93 | */ |
94 | void QSimplex::clearDataStructures() |
95 | { |
96 | if (matrix == nullptr) |
97 | return; |
98 | |
99 | // Matrix |
100 | rows = 0; |
101 | columns = 0; |
102 | firstArtificial = 0; |
103 | free(ptr: matrix); |
104 | matrix = nullptr; |
105 | |
106 | // Constraints |
107 | for (int i = 0; i < constraints.size(); ++i) { |
108 | delete constraints[i]->helper.first; |
109 | delete constraints[i]->artificial; |
110 | delete constraints[i]; |
111 | } |
112 | constraints.clear(); |
113 | |
114 | // Other |
115 | variables.clear(); |
116 | objective = nullptr; |
117 | } |
118 | |
119 | /*! |
120 | \internal |
121 | Sets the new constraints in the simplex solver and returns whether the problem |
122 | is feasible. |
123 | |
124 | This method sets the new constraints, normalizes them, creates the simplex matrix |
125 | and runs the first simplex phase. |
126 | */ |
127 | bool QSimplex::setConstraints(const QList<QSimplexConstraint *> &newConstraints) |
128 | { |
129 | //////////////////////////// |
130 | // Reset to initial state // |
131 | //////////////////////////// |
132 | clearDataStructures(); |
133 | |
134 | if (newConstraints.isEmpty()) |
135 | return true; // we are ok with no constraints |
136 | |
137 | // Make deep copy of constraints. We need this copy because we may change |
138 | // them in the simplification method. |
139 | for (int i = 0; i < newConstraints.size(); ++i) { |
140 | QSimplexConstraint *c = new QSimplexConstraint; |
141 | c->constant = newConstraints[i]->constant; |
142 | c->ratio = newConstraints[i]->ratio; |
143 | c->variables = newConstraints[i]->variables; |
144 | constraints << c; |
145 | } |
146 | |
147 | // Remove constraints of type Var == K and replace them for their value. |
148 | if (!simplifyConstraints(constraints: &constraints)) { |
149 | qWarning(msg: "QSimplex: No feasible solution!" ); |
150 | clearDataStructures(); |
151 | return false; |
152 | } |
153 | |
154 | /////////////////////////////////////// |
155 | // Prepare variables and constraints // |
156 | /////////////////////////////////////// |
157 | |
158 | // Set Variables direct mapping. |
159 | // "variables" is a list that provides a stable, indexed list of all variables |
160 | // used in this problem. |
161 | QSet<QSimplexVariable *> variablesSet; |
162 | for (int i = 0; i < constraints.size(); ++i) { |
163 | const auto &v = constraints.at(i)->variables; |
164 | for (auto it = v.cbegin(), end = v.cend(); it != end; ++it) |
165 | variablesSet.insert(value: it.key()); |
166 | } |
167 | variables = variablesSet.values(); |
168 | |
169 | // Set Variables reverse mapping |
170 | // We also need to be able to find the index for a given variable, to do that |
171 | // we store in each variable its index. |
172 | for (int i = 0; i < variables.size(); ++i) { |
173 | // The variable "0" goes at the column "1", etc... |
174 | variables[i]->index = i + 1; |
175 | } |
176 | |
177 | // Normalize Constraints |
178 | // In this step, we prepare the constraints in two ways: |
179 | // Firstly, we modify all constraints of type "LessOrEqual" or "MoreOrEqual" |
180 | // by the adding slack or surplus variables and making them "Equal" constraints. |
181 | // Secondly, we need every single constraint to have a direct, easy feasible |
182 | // solution. Constraints that have slack variables are already easy to solve, |
183 | // to all the others we add artificial variables. |
184 | // |
185 | // At the end we modify the constraints as follows: |
186 | // - LessOrEqual: SLACK variable is added. |
187 | // - Equal: ARTIFICIAL variable is added. |
188 | // - More or Equal: ARTIFICIAL and SURPLUS variables are added. |
189 | int variableIndex = variables.size(); |
190 | QList <QSimplexVariable *> artificialList; |
191 | |
192 | for (int i = 0; i < constraints.size(); ++i) { |
193 | QSimplexVariable *slack; |
194 | QSimplexVariable *surplus; |
195 | QSimplexVariable *artificial; |
196 | |
197 | Q_ASSERT(constraints[i]->helper.first == 0); |
198 | Q_ASSERT(constraints[i]->artificial == nullptr); |
199 | |
200 | switch(constraints[i]->ratio) { |
201 | case QSimplexConstraint::LessOrEqual: |
202 | slack = new QSimplexVariable; |
203 | slack->index = ++variableIndex; |
204 | constraints[i]->helper.first = slack; |
205 | constraints[i]->helper.second = 1.0; |
206 | break; |
207 | case QSimplexConstraint::MoreOrEqual: |
208 | surplus = new QSimplexVariable; |
209 | surplus->index = ++variableIndex; |
210 | constraints[i]->helper.first = surplus; |
211 | constraints[i]->helper.second = -1.0; |
212 | Q_FALLTHROUGH(); |
213 | case QSimplexConstraint::Equal: |
214 | artificial = new QSimplexVariable; |
215 | constraints[i]->artificial = artificial; |
216 | artificialList += constraints[i]->artificial; |
217 | break; |
218 | } |
219 | } |
220 | |
221 | // All original, slack and surplus have already had its index set |
222 | // at this point. We now set the index of the artificial variables |
223 | // as to ensure they are at the end of the variable list and therefore |
224 | // can be easily removed at the end of this method. |
225 | firstArtificial = variableIndex + 1; |
226 | for (int i = 0; i < artificialList.size(); ++i) |
227 | artificialList[i]->index = ++variableIndex; |
228 | artificialList.clear(); |
229 | |
230 | ///////////////////////////// |
231 | // Fill the Simplex matrix // |
232 | ///////////////////////////// |
233 | |
234 | // One for each variable plus the Basic and BFS columns (first and last) |
235 | columns = variableIndex + 2; |
236 | // One for each constraint plus the objective function |
237 | rows = constraints.size() + 1; |
238 | |
239 | matrix = (qreal *)malloc(size: sizeof(qreal) * columns * rows); |
240 | if (!matrix) { |
241 | qWarning(msg: "QSimplex: Unable to allocate memory!" ); |
242 | return false; |
243 | } |
244 | for (int i = columns * rows - 1; i >= 0; --i) |
245 | matrix[i] = 0.0; |
246 | |
247 | // Fill Matrix |
248 | for (int i = 1; i <= constraints.size(); ++i) { |
249 | QSimplexConstraint *c = constraints[i - 1]; |
250 | |
251 | if (c->artificial) { |
252 | // Will use artificial basic variable |
253 | setValueAt(rowIndex: i, columnIndex: 0, value: c->artificial->index); |
254 | setValueAt(rowIndex: i, columnIndex: c->artificial->index, value: 1.0); |
255 | |
256 | if (c->helper.second != 0.0) { |
257 | // Surplus variable |
258 | setValueAt(rowIndex: i, columnIndex: c->helper.first->index, value: c->helper.second); |
259 | } |
260 | } else { |
261 | // Slack is used as the basic variable |
262 | Q_ASSERT(c->helper.second == 1.0); |
263 | setValueAt(rowIndex: i, columnIndex: 0, value: c->helper.first->index); |
264 | setValueAt(rowIndex: i, columnIndex: c->helper.first->index, value: 1.0); |
265 | } |
266 | |
267 | QHash<QSimplexVariable *, qreal>::const_iterator iter; |
268 | for (iter = c->variables.constBegin(); |
269 | iter != c->variables.constEnd(); |
270 | ++iter) { |
271 | setValueAt(rowIndex: i, columnIndex: iter.key()->index, value: iter.value()); |
272 | } |
273 | |
274 | setValueAt(rowIndex: i, columnIndex: columns - 1, value: c->constant); |
275 | } |
276 | |
277 | // Set objective for the first-phase Simplex. |
278 | // Z = -1 * sum_of_artificial_vars |
279 | for (int j = firstArtificial; j < columns - 1; ++j) |
280 | setValueAt(rowIndex: 0, columnIndex: j, value: 1.0); |
281 | |
282 | // Maximize our objective (artificial vars go to zero) |
283 | solveMaxHelper(); |
284 | |
285 | // If there is a solution where the sum of all artificial |
286 | // variables is zero, then all of them can be removed and yet |
287 | // we will have a feasible (but not optimal) solution for the |
288 | // original problem. |
289 | // Otherwise, we clean up our structures and report there is |
290 | // no feasible solution. |
291 | if ((valueAt(rowIndex: 0, columnIndex: columns - 1) != 0.0) && (qAbs(t: valueAt(rowIndex: 0, columnIndex: columns - 1)) > 0.00001)) { |
292 | qWarning(msg: "QSimplex: No feasible solution!" ); |
293 | clearDataStructures(); |
294 | return false; |
295 | } |
296 | |
297 | // Remove artificial variables. We already have a feasible |
298 | // solution for the first problem, thus we don't need them |
299 | // anymore. |
300 | clearColumns(first: firstArtificial, last: columns - 2); |
301 | |
302 | return true; |
303 | } |
304 | |
305 | /*! |
306 | \internal |
307 | |
308 | Run simplex on the current matrix with the current objective. |
309 | |
310 | This is the iterative method. The matrix lines are combined |
311 | as to modify the variable values towards the best solution possible. |
312 | The method returns when the matrix is in the optimal state. |
313 | */ |
314 | void QSimplex::solveMaxHelper() |
315 | { |
316 | reducedRowEchelon(); |
317 | while (iterate()) ; |
318 | } |
319 | |
320 | /*! |
321 | \internal |
322 | */ |
323 | void QSimplex::setObjective(QSimplexConstraint *newObjective) |
324 | { |
325 | objective = newObjective; |
326 | } |
327 | |
328 | /*! |
329 | \internal |
330 | */ |
331 | void QSimplex::clearRow(int rowIndex) |
332 | { |
333 | qreal *item = matrix + rowIndex * columns; |
334 | for (int i = 0; i < columns; ++i) |
335 | item[i] = 0.0; |
336 | } |
337 | |
338 | /*! |
339 | \internal |
340 | */ |
341 | void QSimplex::clearColumns(int first, int last) |
342 | { |
343 | for (int i = 0; i < rows; ++i) { |
344 | qreal *row = matrix + i * columns; |
345 | for (int j = first; j <= last; ++j) |
346 | row[j] = 0.0; |
347 | } |
348 | } |
349 | |
350 | /*! |
351 | \internal |
352 | */ |
353 | void QSimplex::dumpMatrix() |
354 | { |
355 | qDebug(msg: "---- Simplex Matrix ----\n" ); |
356 | |
357 | QString str(QLatin1String(" " )); |
358 | for (int j = 0; j < columns; ++j) |
359 | str += QString::fromLatin1(str: " <%1 >" ).arg(a: j, fieldWidth: 2); |
360 | qDebug(msg: "%s" , qPrintable(str)); |
361 | for (int i = 0; i < rows; ++i) { |
362 | str = QString::fromLatin1(str: "Row %1:" ).arg(a: i, fieldWidth: 2); |
363 | |
364 | qreal *row = matrix + i * columns; |
365 | for (int j = 0; j < columns; ++j) |
366 | str += QString::fromLatin1(str: "%1" ).arg(a: row[j], fieldWidth: 7, fmt: 'f', prec: 2); |
367 | qDebug(msg: "%s" , qPrintable(str)); |
368 | } |
369 | qDebug(msg: "------------------------\n" ); |
370 | } |
371 | |
372 | /*! |
373 | \internal |
374 | */ |
375 | void QSimplex::combineRows(int toIndex, int fromIndex, qreal factor) |
376 | { |
377 | if (!factor) |
378 | return; |
379 | |
380 | qreal *from = matrix + fromIndex * columns; |
381 | qreal *to = matrix + toIndex * columns; |
382 | |
383 | for (int j = 1; j < columns; ++j) { |
384 | qreal value = from[j]; |
385 | |
386 | // skip to[j] = to[j] + factor*0.0 |
387 | if (value == 0.0) |
388 | continue; |
389 | |
390 | to[j] += factor * value; |
391 | |
392 | // ### Avoid Numerical errors |
393 | if (qAbs(t: to[j]) < 0.0000000001) |
394 | to[j] = 0.0; |
395 | } |
396 | } |
397 | |
398 | /*! |
399 | \internal |
400 | */ |
401 | int QSimplex::findPivotColumn() |
402 | { |
403 | qreal min = 0; |
404 | int minIndex = -1; |
405 | |
406 | for (int j = 0; j < columns-1; ++j) { |
407 | if (valueAt(rowIndex: 0, columnIndex: j) < min) { |
408 | min = valueAt(rowIndex: 0, columnIndex: j); |
409 | minIndex = j; |
410 | } |
411 | } |
412 | |
413 | return minIndex; |
414 | } |
415 | |
416 | /*! |
417 | \internal |
418 | |
419 | For a given pivot column, find the pivot row. That is, the row with the |
420 | minimum associated "quotient" where: |
421 | |
422 | - quotient is the division of the value in the last column by the value |
423 | in the pivot column. |
424 | - rows with value less or equal to zero are ignored |
425 | - if two rows have the same quotient, lines are chosen based on the |
426 | highest variable index (value in the first column) |
427 | |
428 | The last condition avoids a bug where artificial variables would be |
429 | left behind for the second-phase simplex, and with 'good' |
430 | constraints would be removed before it, what would lead to incorrect |
431 | results. |
432 | */ |
433 | int QSimplex::pivotRowForColumn(int column) |
434 | { |
435 | qreal min = qreal(999999999999.0); // ### |
436 | int minIndex = -1; |
437 | |
438 | for (int i = 1; i < rows; ++i) { |
439 | qreal divisor = valueAt(rowIndex: i, columnIndex: column); |
440 | if (divisor <= 0) |
441 | continue; |
442 | |
443 | qreal quotient = valueAt(rowIndex: i, columnIndex: columns - 1) / divisor; |
444 | if (quotient < min) { |
445 | min = quotient; |
446 | minIndex = i; |
447 | } else if ((quotient == min) && (valueAt(rowIndex: i, columnIndex: 0) > valueAt(rowIndex: minIndex, columnIndex: 0))) { |
448 | minIndex = i; |
449 | } |
450 | } |
451 | |
452 | return minIndex; |
453 | } |
454 | |
455 | /*! |
456 | \internal |
457 | */ |
458 | void QSimplex::reducedRowEchelon() |
459 | { |
460 | for (int i = 1; i < rows; ++i) { |
461 | int factorInObjectiveRow = valueAt(rowIndex: i, columnIndex: 0); |
462 | combineRows(toIndex: 0, fromIndex: i, factor: -1 * valueAt(rowIndex: 0, columnIndex: factorInObjectiveRow)); |
463 | } |
464 | } |
465 | |
466 | /*! |
467 | \internal |
468 | |
469 | Does one iteration towards a better solution for the problem. |
470 | See 'solveMaxHelper'. |
471 | */ |
472 | bool QSimplex::iterate() |
473 | { |
474 | // Find Pivot column |
475 | int pivotColumn = findPivotColumn(); |
476 | if (pivotColumn == -1) |
477 | return false; |
478 | |
479 | // Find Pivot row for column |
480 | int pivotRow = pivotRowForColumn(column: pivotColumn); |
481 | if (pivotRow == -1) { |
482 | qWarning(msg: "QSimplex: Unbounded problem!" ); |
483 | return false; |
484 | } |
485 | |
486 | // Normalize Pivot Row |
487 | qreal pivot = valueAt(rowIndex: pivotRow, columnIndex: pivotColumn); |
488 | if (pivot != 1.0) |
489 | combineRows(toIndex: pivotRow, fromIndex: pivotRow, factor: (1.0 - pivot) / pivot); |
490 | |
491 | // Update other rows |
492 | for (int row=0; row < rows; ++row) { |
493 | if (row == pivotRow) |
494 | continue; |
495 | |
496 | combineRows(toIndex: row, fromIndex: pivotRow, factor: -1 * valueAt(rowIndex: row, columnIndex: pivotColumn)); |
497 | } |
498 | |
499 | // Update first column |
500 | setValueAt(rowIndex: pivotRow, columnIndex: 0, value: pivotColumn); |
501 | |
502 | // dumpMatrix(); |
503 | // qDebug("------------ end of iteration --------------\n"); |
504 | return true; |
505 | } |
506 | |
507 | /*! |
508 | \internal |
509 | |
510 | Both solveMin and solveMax are interfaces to this method. |
511 | |
512 | The enum SolverFactor admits 2 values: Minimum (-1) and Maximum (+1). |
513 | |
514 | This method sets the original objective and runs the second phase |
515 | Simplex to obtain the optimal solution for the problem. As the internal |
516 | simplex solver is only able to _maximize_ objectives, we handle the |
517 | minimization case by inverting the original objective and then |
518 | maximizing it. |
519 | */ |
520 | qreal QSimplex::solver(SolverFactor factor) |
521 | { |
522 | // Remove old objective |
523 | clearRow(rowIndex: 0); |
524 | |
525 | // Set new objective in the first row of the simplex matrix |
526 | qreal resultOffset = 0; |
527 | QHash<QSimplexVariable *, qreal>::const_iterator iter; |
528 | for (iter = objective->variables.constBegin(); |
529 | iter != objective->variables.constEnd(); |
530 | ++iter) { |
531 | |
532 | // Check if the variable was removed in the simplification process. |
533 | // If so, we save its offset to the objective function and skip adding |
534 | // it to the matrix. |
535 | if (iter.key()->index == -1) { |
536 | resultOffset += iter.value() * iter.key()->result; |
537 | continue; |
538 | } |
539 | |
540 | setValueAt(rowIndex: 0, columnIndex: iter.key()->index, value: -1 * factor * iter.value()); |
541 | } |
542 | |
543 | solveMaxHelper(); |
544 | collectResults(); |
545 | |
546 | #ifdef QT_DEBUG |
547 | for (int i = 0; i < constraints.size(); ++i) { |
548 | Q_ASSERT(constraints[i]->isSatisfied()); |
549 | } |
550 | #endif |
551 | |
552 | // Return the value calculated by the simplex plus the value of the |
553 | // fixed variables. |
554 | return (factor * valueAt(rowIndex: 0, columnIndex: columns - 1)) + resultOffset; |
555 | } |
556 | |
557 | /*! |
558 | \internal |
559 | Minimize the original objective. |
560 | */ |
561 | qreal QSimplex::solveMin() |
562 | { |
563 | return solver(factor: Minimum); |
564 | } |
565 | |
566 | /*! |
567 | \internal |
568 | Maximize the original objective. |
569 | */ |
570 | qreal QSimplex::solveMax() |
571 | { |
572 | return solver(factor: Maximum); |
573 | } |
574 | |
575 | /*! |
576 | \internal |
577 | |
578 | Reads results from the simplified matrix and saves them in the |
579 | "result" member of each QSimplexVariable. |
580 | */ |
581 | void QSimplex::collectResults() |
582 | { |
583 | // All variables are zero unless overridden below. |
584 | |
585 | // ### Is this really needed? Is there any chance that an |
586 | // important variable remains as non-basic at the end of simplex? |
587 | for (int i = 0; i < variables.size(); ++i) |
588 | variables[i]->result = 0; |
589 | |
590 | // Basic variables |
591 | // Update the variable indicated in the first column with the value |
592 | // in the last column. |
593 | for (int i = 1; i < rows; ++i) { |
594 | int index = valueAt(rowIndex: i, columnIndex: 0) - 1; |
595 | if (index < variables.size()) |
596 | variables[index]->result = valueAt(rowIndex: i, columnIndex: columns - 1); |
597 | } |
598 | } |
599 | |
600 | /*! |
601 | \internal |
602 | |
603 | Looks for single-valued variables and remove them from the constraints list. |
604 | */ |
605 | bool QSimplex::simplifyConstraints(QList<QSimplexConstraint *> *constraints) |
606 | { |
607 | QHash<QSimplexVariable *, qreal> results; // List of single-valued variables |
608 | bool modified = true; // Any chance more optimization exists? |
609 | |
610 | while (modified) { |
611 | modified = false; |
612 | |
613 | // For all constraints |
614 | QList<QSimplexConstraint *>::iterator iter = constraints->begin(); |
615 | while (iter != constraints->end()) { |
616 | QSimplexConstraint *c = *iter; |
617 | if ((c->ratio == QSimplexConstraint::Equal) && (c->variables.count() == 1)) { |
618 | // Check whether this is a constraint of type Var == K |
619 | // If so, save its value to "results". |
620 | QSimplexVariable *variable = c->variables.constBegin().key(); |
621 | qreal result = c->constant / c->variables.value(akey: variable); |
622 | |
623 | results.insert(akey: variable, avalue: result); |
624 | variable->result = result; |
625 | variable->index = -1; |
626 | modified = true; |
627 | |
628 | } |
629 | |
630 | // Replace known values among their variables |
631 | QHash<QSimplexVariable *, qreal>::const_iterator r; |
632 | for (r = results.constBegin(); r != results.constEnd(); ++r) { |
633 | if (c->variables.contains(akey: r.key())) { |
634 | c->constant -= r.value() * c->variables.take(akey: r.key()); |
635 | modified = true; |
636 | } |
637 | } |
638 | |
639 | // Keep it normalized |
640 | if (c->constant < 0) |
641 | c->invert(); |
642 | |
643 | if (c->variables.isEmpty()) { |
644 | // If constraint became empty due to substitution, delete it. |
645 | if (c->isSatisfied() == false) |
646 | // We must ensure that the constraint soon to be deleted would not |
647 | // make the problem unfeasible if left behind. If that's the case, |
648 | // we return false so the simplex solver can properly report that. |
649 | return false; |
650 | |
651 | delete c; |
652 | iter = constraints->erase(it: iter); |
653 | } else { |
654 | ++iter; |
655 | } |
656 | } |
657 | } |
658 | |
659 | return true; |
660 | } |
661 | |
662 | void QSimplexConstraint::invert() |
663 | { |
664 | constant = -constant; |
665 | ratio = Ratio(2 - ratio); |
666 | |
667 | QHash<QSimplexVariable *, qreal>::iterator iter; |
668 | for (iter = variables.begin(); iter != variables.end(); ++iter) { |
669 | iter.value() = -iter.value(); |
670 | } |
671 | } |
672 | |
673 | QT_END_NAMESPACE |
674 | |