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https://github.com/ethereum/solidity
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Turn into class.
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@ -381,225 +381,6 @@ pair<LPResult, vector<rational>> simplex(vector<Constraint> _constraints, Linear
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return make_pair(result, solutionVector(tableau));
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}
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/// Introduces a new variable for each now and returns
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/// a map from the indices of those variables
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/// to the constraint they correspond to.
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map<size_t, size_t> normalizeForSolvingWithBounds(SolvingState& _state)
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{
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size_t varsNeeded = _state.constraints.size();
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/*
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for (Constraint& c: _state.constraints)
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if (!c.equality || c.data[0])
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varsNeeded++;
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*/
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map<size_t, size_t> basicVariables;
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size_t row = 0;
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for (Constraint& c: _state.constraints)
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{
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c.data.resize(_state.variableNames.size() + varsNeeded);
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/*
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if (c.equality && !c.data[0])
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continue;
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*/
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// ax + by <= c
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// -> ax + by - s = 0, 0 <= s <= c
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// ax + by = c
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// -> ax + by - s = 0, c <= s <= c
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size_t newVarIndex = _state.variableNames.size();
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basicVariables[newVarIndex] = row++;
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solAssert(_state.variableNames.size() == _state.bounds.size());
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// TODO name needed unique?
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_state.variableNames.emplace_back("_s" + to_string(newVarIndex));
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_state.bounds.emplace_back(SolvingState::Bounds{
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{c.equality ? rational{c.data[0]} : rational{0}},
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{c.data[0]},
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{},
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{}
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});
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c.equality = true;
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solAssert(c.data.size() > newVarIndex);
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c.data[newVarIndex] = -1;
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c.data[0] = 0;
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}
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return basicVariables;
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}
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void withBoundsUpdate(
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SolvingState& _state,
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vector<rational>& _assignments,
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map<size_t, size_t> const& _basicVariables,
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size_t _i,
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rational const& _value
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)
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{
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rational delta = _value - _assignments[_i];
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_assignments[_i] = _value;
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for (size_t j = 0; j < _assignments.size(); j++)
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if (_basicVariables.count(j) && _state.constraints[_basicVariables.at(j)].data[_i])
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_assignments[j] += _state.constraints[_basicVariables.at(j)].data[_i] * delta;
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}
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optional<size_t> firstConflictingBasicVariable(
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SolvingState& _state,
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vector<rational>& _assignments,
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map<size_t, size_t> const& _basicVariables
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)
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{
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for (auto const& [i, bounds]: _state.bounds | ranges::views::enumerate)
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if (_basicVariables.count(i) && (
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(bounds.lower && _assignments[i] < *bounds.lower) ||
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(bounds.upper && _assignments[i] > *bounds.upper)
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))
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return i;
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return nullopt;
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}
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optional<size_t> firstReplacementVar(
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SolvingState& _state,
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vector<rational>& _assignments,
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map<size_t, size_t> const& _basicVariables,
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size_t _basicVarToReplace,
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bool _increasing
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)
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{
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LinearExpression const& basicVarEquation = _state.constraints[_basicVariables.at(_basicVarToReplace)].data;
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for (auto const& [i, bounds]: _state.bounds | ranges::views::enumerate)
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{
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if (_basicVariables.count(i) || !basicVarEquation[i])
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continue;
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bool positive = basicVarEquation[i] > 0;
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if (!_increasing)
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positive = !positive;
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if (positive && (!_state.bounds[i].upper || _assignments[i] < _state.bounds[i].upper))
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return i;
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if (!positive && (!_state.bounds[i].lower || _assignments[i] > _state.bounds[i].lower))
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return i;
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}
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return nullopt;
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}
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void pivot(SolvingState& _state, map<size_t, size_t>& _basicVariables, size_t _old, size_t _new)
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{
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// Transform pivotRow such that the coefficient for _new is -1
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// Then use that to set all other coefficients for _new to zero.
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size_t pivotRow = _basicVariables[_old];
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LinearExpression& pivotRowData = _state.constraints[_basicVariables[_old]].data;
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rational pivot = pivotRowData[_new];
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solAssert(pivot != 0, "");
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if (pivot != -1)
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pivotRowData /= -pivot;
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solAssert(pivotRowData[_new] == rational(-1), "");
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auto subtractMultipleOfPivotRow = [&](LinearExpression& _row) {
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if (_row[_new] == 0)
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return;
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else if (_row[_new] == rational{1})
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_row += pivotRowData;
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else if (_row[_new] == rational{-1})
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_row -= pivotRowData;
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else
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_row += _row[_new] * pivotRowData;
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};
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for (size_t i = 0; i < _state.constraints.size(); ++i)
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if (i != pivotRow)
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subtractMultipleOfPivotRow(_state.constraints[i].data);
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_basicVariables.erase(_old);
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_basicVariables[_new] = pivotRow;
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}
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void pivotAndUpdate(
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SolvingState& _state,
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map<size_t, size_t>& _basicVariables,
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vector<rational>& _assignments,
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size_t _oldBasicVar,
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rational const& _newValue,
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size_t _newBasicVar
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)
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{
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rational theta = (_newValue - _assignments[_oldBasicVar]) / _state.constraints[_basicVariables[_oldBasicVar]].data[_newBasicVar];
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_assignments[_oldBasicVar] = _newValue;
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_assignments[_newBasicVar] += theta;
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for (auto const& [i, row]: _basicVariables)
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if (i != _oldBasicVar && _state.constraints[row].data[_newBasicVar])
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_assignments[i] += _state.constraints[row].data[_newBasicVar] * theta;
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pivot(_state, _basicVariables, _oldBasicVar, _newBasicVar);
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cout << "After pivot and update: " << endl << _state.toString() << endl;
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}
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pair<LPResult, vector<rational>> simplexWithBounds(SolvingState _state)
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{
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cout << "===========================" << endl;
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cout << "===========================" << endl;
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cout << "simpl with bounds on\n" << _state.toString() << endl;
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map<size_t, size_t> basicVariables = normalizeForSolvingWithBounds(_state);
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cout << "After norm ------------------------\n" << _state.toString() << endl;
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vector<rational> assignments(_state.variableNames.size());
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// We start with an all-zero assignment and then gradually add
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// the bounds we already have.
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cout << "Adjusting bounds on non-basic variables\n";
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// Adjust the assignments so we satisfy the bounds of the non-basic variables.
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for (auto const& [i, bounds]: _state.bounds | ranges::views::enumerate)
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{
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if (basicVariables.count(i) || (!bounds.lower && !bounds.upper))
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continue;
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if (bounds.lower && bounds.upper)
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solAssert(*bounds.lower <= *bounds.upper);
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if (bounds.lower && assignments[i] < *bounds.lower)
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withBoundsUpdate(_state, assignments, basicVariables, i, *bounds.lower);
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else if (bounds.upper && assignments[i] > *bounds.upper)
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withBoundsUpdate(_state, assignments, basicVariables, i, *bounds.upper);
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cout << "Assignments after satisfying bound for " << _state.variableNames[i] << ":\n";
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for (auto const& [j, val]: assignments | ranges::views::enumerate)
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{
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cout << " - " << _state.variableNames[j];
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if (basicVariables.count(j)) cout << " (b)";
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cout << " = " << ::toString(val) << endl;
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}
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cout << "----------------\n" << _state.toString() << endl;
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}
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cout << "Bounds on non-basic vaiables set.\n";
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// Now try to make the basic variables happy, pivoting if necessary.
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// TODO bound number of iterations
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while (auto bvi = firstConflictingBasicVariable(_state, assignments, basicVariables))
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{
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cout << "Basic variable " << _state.variableNames[*bvi] << " is conflicting." << endl;
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if (_state.bounds[*bvi].lower && assignments[*bvi] < *_state.bounds[*bvi].lower)
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{
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if (auto replacementVar = firstReplacementVar(_state, assignments, basicVariables, *bvi, true))
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pivotAndUpdate(_state, basicVariables, assignments, *bvi, *_state.bounds.at(*bvi).lower, *replacementVar);
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else
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return make_pair(LPResult::Infeasible, vector<rational>{});
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}
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else if (_state.bounds[*bvi].upper && assignments[*bvi] > *_state.bounds[*bvi].upper)
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{
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if (auto replacementVar = firstReplacementVar(_state, assignments, basicVariables, *bvi, false))
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pivotAndUpdate(_state, basicVariables, assignments, *bvi, *_state.bounds.at(*bvi).upper, *replacementVar);
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else
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return make_pair(LPResult::Infeasible, vector<rational>{});
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}
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}
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cout << ">>>>>>>>>>>>>>>>>>>>>>" << endl;
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cout << ">>>>>>>>>>>>>>>>>>>>>>" << endl;
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return make_pair(LPResult::Feasible, move(assignments));
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}
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/// Turns all bounds into constraints.
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/// @returns false if the bounds make the state infeasible.
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optional<ReasonSet> boundsToConstraints(SolvingState& _state)
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@ -819,6 +600,199 @@ string SolvingState::toString() const
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return result;
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}
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SimplexWithBounds::SimplexWithBounds(SolvingState _state):
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m_state(move(_state))
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{
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size_t varsNeeded = m_state.constraints.size();
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size_t row = 0;
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for (Constraint& c: m_state.constraints)
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{
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c.data.resize(m_state.variableNames.size() + varsNeeded);
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size_t newVarIndex = m_state.variableNames.size();
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m_basicVariables[newVarIndex] = row++;
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solAssert(m_state.variableNames.size() == m_state.bounds.size());
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// TODO name needed unique?
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m_state.variableNames.emplace_back("_s" + to_string(newVarIndex));
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// TODO we assume zero as lower bound here, but we do not have to.
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m_state.bounds.emplace_back(SolvingState::Bounds{
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{c.equality ? rational{c.data[0]} : rational{0}},
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{c.data[0]},
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{},
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{}
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});
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c.equality = true;
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solAssert(c.data.size() > newVarIndex);
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c.data[newVarIndex] = -1;
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c.data[0] = 0;
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}
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m_assignments.resize(m_state.variableNames.size());
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}
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LPResult SimplexWithBounds::check()
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{
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// cout << "===========================" << endl;
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// cout << "===========================" << endl;
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// cout << "simpl with bounds on\n" << toString() << endl;
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// We start with an all-zero assignment and then gradually add
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// the bounds we already have.
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//cout << "Adjusting bounds on non-basic variables\n";
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// Adjust the assignments so we satisfy the bounds of the non-basic variables.
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for (auto const& [i, bounds]: m_state.bounds | ranges::views::enumerate)
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{
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if (m_basicVariables.count(i) || (!bounds.lower && !bounds.upper))
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continue;
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if (bounds.lower && bounds.upper)
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solAssert(*bounds.lower <= *bounds.upper);
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if (bounds.lower && m_assignments[i] < *bounds.lower)
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update(i, *bounds.lower);
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else if (bounds.upper && m_assignments[i] > *bounds.upper)
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update(i, *bounds.upper);
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}
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//cout << "Bounds on non-basic vaiables set.\n" << toString() << endl;
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// Now try to make the basic variables happy, pivoting if necessary.
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// TODO bound number of iterations
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while (auto bvi = firstConflictingBasicVariable())
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{
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//cout << "Basic variable " << m_state.variableNames[*bvi] << " is conflicting." << endl;
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if (m_state.bounds[*bvi].lower && m_assignments[*bvi] < *m_state.bounds[*bvi].lower)
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{
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if (auto replacementVar = firstReplacementVar(*bvi, true))
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pivotAndUpdate(*bvi, *m_state.bounds.at(*bvi).lower, *replacementVar);
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else
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{
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//cout << "------->>>>>>>>>>>>>> infeasible\n";
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return LPResult::Infeasible;
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}
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}
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else if (m_state.bounds[*bvi].upper && m_assignments[*bvi] > *m_state.bounds[*bvi].upper)
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{
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if (auto replacementVar = firstReplacementVar(*bvi, false))
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pivotAndUpdate(*bvi, *m_state.bounds.at(*bvi).upper, *replacementVar);
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else
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{
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//cout << "------->>>>>>>>>>>>>> infeasible\n";
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return LPResult::Infeasible;
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}
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}
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}
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//cout << "SAT ------->>>>>>>>>>>>>>\n";
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return LPResult::Feasible;
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}
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void SimplexWithBounds::update(size_t _var, rational const& _value)
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{
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rational delta = _value - m_assignments[_var];
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m_assignments[_var] = _value;
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for (size_t j = 0; j < m_assignments.size(); j++)
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if (m_basicVariables.count(j) && m_state.constraints[m_basicVariables.at(j)].data[_var])
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m_assignments[j] += m_state.constraints[m_basicVariables.at(j)].data[_var] * delta;
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}
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optional<size_t> SimplexWithBounds::firstConflictingBasicVariable() const
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{
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for (auto const& [i, bounds]: m_state.bounds | ranges::views::enumerate)
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if (m_basicVariables.count(i) && (
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(bounds.lower && m_assignments[i] < *bounds.lower) ||
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(bounds.upper && m_assignments[i] > *bounds.upper)
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))
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return i;
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return nullopt;
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}
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optional<size_t> SimplexWithBounds::firstReplacementVar(
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size_t _basicVarToReplace,
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bool _increasing
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) const
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{
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LinearExpression const& basicVarEquation = m_state.constraints[m_basicVariables.at(_basicVarToReplace)].data;
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for (auto const& [i, bounds]: m_state.bounds | ranges::views::enumerate)
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{
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if (m_basicVariables.count(i) || !basicVarEquation[i])
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continue;
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bool positive = basicVarEquation[i] > 0;
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if (!_increasing)
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positive = !positive;
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if (positive && (!m_state.bounds[i].upper || m_assignments[i] < m_state.bounds[i].upper))
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return i;
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if (!positive && (!m_state.bounds[i].lower || m_assignments[i] > m_state.bounds[i].lower))
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return i;
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}
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return nullopt;
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}
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void SimplexWithBounds::pivot(size_t _old, size_t _new)
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{
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// Transform pivotRow such that the coefficient for _new is -1
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// Then use that to set all other coefficients for _new to zero.
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size_t pivotRow = m_basicVariables[_old];
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LinearExpression& pivotRowData = m_state.constraints[m_basicVariables[_old]].data;
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rational pivot = pivotRowData[_new];
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solAssert(pivot != 0, "");
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if (pivot != -1)
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pivotRowData /= -pivot;
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solAssert(pivotRowData[_new] == rational(-1), "");
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auto subtractMultipleOfPivotRow = [&](LinearExpression& _row) {
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if (_row[_new] == 0)
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return;
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else if (_row[_new] == rational{1})
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_row += pivotRowData;
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else if (_row[_new] == rational{-1})
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_row -= pivotRowData;
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else
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_row += _row[_new] * pivotRowData;
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};
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for (size_t i = 0; i < m_state.constraints.size(); ++i)
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if (i != pivotRow)
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subtractMultipleOfPivotRow(m_state.constraints[i].data);
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m_basicVariables.erase(_old);
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m_basicVariables[_new] = pivotRow;
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}
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void SimplexWithBounds::pivotAndUpdate(
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size_t _oldBasicVar,
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rational const& _newValue,
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size_t _newBasicVar
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)
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{
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rational theta = (_newValue - m_assignments[_oldBasicVar]) / m_state.constraints[m_basicVariables[_oldBasicVar]].data[_newBasicVar];
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m_assignments[_oldBasicVar] = _newValue;
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m_assignments[_newBasicVar] += theta;
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for (auto const& [i, row]: m_basicVariables)
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if (i != _oldBasicVar && m_state.constraints[row].data[_newBasicVar])
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m_assignments[i] += m_state.constraints[row].data[_newBasicVar] * theta;
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pivot(_oldBasicVar, _newBasicVar);
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//cout << "After pivot and update: " << endl << toString() << endl;
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}
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string SimplexWithBounds::toString() const
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{
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string ret = "---\n" + m_state.toString();
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for (auto const& [j, val]: m_assignments | ranges::views::enumerate)
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{
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ret += " " + m_state.variableNames[j];
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if (m_basicVariables.count(j)) ret += " (b)";
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ret += " = " + ::toString(val) + "\n";
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}
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ret += "------\n";
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return ret;
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}
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pair<LPResult, variant<map<size_t, rational>, ReasonSet>> SolvingStateSimplifier::simplify()
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{
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do
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@ -1150,8 +1124,7 @@ pair<LPResult, variant<Model, ReasonSet>> LPSolver::check()
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}
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if (!result)
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{
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result = LPResult::Unknown;
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tie(*result, problem->model) = simplexWithBounds(state);
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*result = SimplexWithBounds{state}.check();
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// TODO we should even keep the updated tableau in the subproblem
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if (m_cache)
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{
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@ -1243,6 +1216,7 @@ void LPSolver::addConstraintToSubProblem(size_t _subProblem, Constraint _constra
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m_subProblemsPerVariable[index] = _subProblem;
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problem.variables.emplace(index);
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}
|
||||
// TODO if we keep the matrix, we could just add this as a new row.
|
||||
problem.removableConstraints.emplace_back(move(_constraint));
|
||||
}
|
||||
|
||||
|
@ -172,6 +172,30 @@ enum class LPResult
|
||||
};
|
||||
|
||||
|
||||
class SimplexWithBounds
|
||||
{
|
||||
public:
|
||||
explicit SimplexWithBounds(SolvingState _state);
|
||||
LPResult check();
|
||||
|
||||
std::string toString() const;
|
||||
private:
|
||||
/// Set value of non-basic variable.
|
||||
void update(size_t _var, rational const& _value);
|
||||
/// @returns the index of the first basic variable violating its bounds.
|
||||
std::optional<size_t> firstConflictingBasicVariable() const;
|
||||
std::optional<size_t> firstReplacementVar(size_t _basicVarToReplace, bool _increasing) const;
|
||||
|
||||
void pivot(size_t _old, size_t _new);
|
||||
void pivotAndUpdate(size_t _oldBasicVar, rational const& _newValue, size_t _newBasicVar);
|
||||
|
||||
SolvingState m_state;
|
||||
std::vector<rational> m_assignments;
|
||||
/// Variable index to row it controls.
|
||||
std::map<size_t, size_t> m_basicVariables;
|
||||
};
|
||||
|
||||
|
||||
/**
|
||||
* Applies several strategies to simplify a given solving state.
|
||||
* During these simplifications, it can sometimes already be determined if the
|
||||
|
Loading…
Reference in New Issue
Block a user