private static bool ModificatedDualIteration() { var vectorCollection = new List<Vector<double>>(); foreach (var item in _task.Jb) { vectorCollection.Add(_task.A.Column(item)); } var aBMatrix = DenseMatrix.OfColumnVectors(vectorCollection.ToArray()); var bMatrix = aBMatrix.Inverse(); // Step3 var kappaList = bMatrix * _task.b; Vector<double> allKappaList = new DenseVector(_task.A.ColumnCount, 0); for (int i = 0; i < allKappaList.Count; i++) { if (_JNbUpper.Contains(i)) { allKappaList[i] = _task.dLower[i]; } else if (_JNbLower.Contains(i)) { allKappaList[i] = _task.dUpper[i]; } else { allKappaList[i] = 0; } } kappaList = bMatrix * (_task.b - _task.A * allKappaList); for (int i = 0; i < _task.Jb.Count; i++) { allKappaList[_task.Jb[i]] = kappaList[i]; } // Step3 double kappaValue = 0; int kappaIndex = 0; var check = false; for (int i = 0; i < allKappaList.Count; i++) { if (allKappaList[i] > _task.dUpper[i] || allKappaList[i] < _task.dLower[i]) { check = true; kappaValue = allKappaList[i]; kappaIndex = i; break; } } if (!check) { _task.xo = allKappaList; //Logger.Log("Stopped at third step"); _stopStep = 3; return false; } // Step4 is unnecessary // Step5 var nk = kappaValue < _task.dLower[kappaIndex] ? 1 : -1; var deltaYT = nk * DenseVector.Create(_task.Jb.Count, i => i == _task.Jb.ToList().IndexOf(kappaIndex) ? 1 : 0) * DenseMatrix.OfColumnVectors(vectorCollection.ToArray()).Inverse(); var nVector = new DenseVector(_task.A.ColumnCount); for (int i = 0; i < _task.A.ColumnCount; i++) { if (!_task.Jb.Contains(i)) { nVector[i] = (deltaYT * _task.A.Column(i)); } } // Step6 Vector<double> sigmaVector = new DenseVector(_task.A.ColumnCount); for (int i = 0; i < sigmaVector.Count; i++) { if (_task.dLower[i] == _task.dUpper[i]) { sigmaVector[i] = double.PositiveInfinity; } else if (_JNbUpper.Contains(i) && nVector[i] < Eps) { sigmaVector[i] = -deltas[i] / nVector[i]; } else if (_JNbLower.Contains(i) && nVector[i] > Eps) { sigmaVector[i] = -deltas[i] / nVector[i]; } else { sigmaVector[i] = double.PositiveInfinity; } } var sigma0 = sigmaVector.Min(); var sigma0Index = sigmaVector.MinimumIndex(); // Step7 if (sigma0 == double.PositiveInfinity) { //Logger.Log("Stopped at seventh step"); _stopStep = 7; return false; } // Step8 Vector<double> newDeltas = new DenseVector(_task.A.ColumnCount); for (int i = 0; i < newDeltas.Count; i++) { if (_task.Jb.Contains(i) && i != kappaIndex) { newDeltas[i] = 0; } else if (i == kappaIndex) { newDeltas[i] = sigma0 * nk; } else { newDeltas[i] = deltas[i] + sigma0 * nVector[i]; } } deltas = newDeltas.ToList(); // Step9 _task.Jb[_task.Jb.ToList().IndexOf(kappaIndex)] = sigma0Index; // Step10 if (nk == 1.0) { if (_JNbUpper.Contains(sigma0Index)) { _JNbUpper[_JNbUpper.IndexOf(sigma0Index)] = kappaIndex; } else { _JNbUpper.Add(kappaIndex); } } else if (nk == -1.0) { if (_JNbUpper.Contains(sigma0Index)) { _JNbUpper.Remove(sigma0Index); } } _JNbLower.Clear(); for (int i = 0; i < _task.A.ColumnCount; i++) { if (!_JNbUpper.Contains(i) && !_task.Jb.Contains(i)) { _JNbLower.Add(i); } } return true; }
private static bool DualIteration() { // Step1 var vectorCollection = new List<Vector<double>>(); foreach (var item in _Jb) { vectorCollection.Add(_A.Column(item)); } var aBMatrix = DenseMatrix.OfColumnVectors(vectorCollection.ToArray()); var bMatrix = aBMatrix.Inverse(); var kappa = bMatrix * _b; // Step2 if (kappa.ToList().TrueForAll(x => x >= Eps)) { //Logger.Log("Stopped at second step"); return false; } // Step3 var minJ = kappa.MinimumIndex(); var deltaYT = DenseVector.Create(_Jb.Length, i => i == minJ ? 1 : 0) * DenseMatrix.OfColumnVectors(vectorCollection.ToArray()).Inverse(); var nVector = new DenseVector(_A.ColumnCount); for (int i = 0; i < _A.ColumnCount; i++) { if (!_Jb.Contains(i)) { nVector[i] = (deltaYT * _A.Column(i)); } } if (nVector.ToList().TrueForAll(n => n >= Eps)) { //Logger.Log("Stopped at third step"); return false; } // Step4 double sigma0 = Double.PositiveInfinity; int sigmaIndex = 0; var sigmaList = new DenseVector(_A.ColumnCount); for (int i = 0, j = 0; i < _A.ColumnCount; i++) { if (!_Jb.Contains(i) && (nVector[i] < 0)) { sigmaList[i] = ((_C[i] - _A.Column(i) * _Yb) / nVector[i]); if (sigmaList[i] < sigma0) { sigma0 = sigmaList[i]; sigmaIndex = i; } } } // Step5 var newYb = _Yb.Add(sigma0 * deltaYT); _Yb = newYb; _Jb[minJ] = sigmaIndex; return true; }