Code to run the examples

Octave code to run the examples. More...

Files
file	run0703.m
	Runs example 7.3 with Newton's method, one variable.
file	run0704.m
	Runs example 7.4 with Newton's method, one variable.
file	run0705.m
	Runs example 7.5 with Newton's method, one variable.
file	run0711.m
	Runs example 7.11 with Newton's method, n variables.
file	run0712.m
	Runs example 7.12 with Newton's method, n variables.
file	runMachineEpsilon.m
	Calculate the machine epsilon.
file	run0703df.m
	Runs example 7.3 with Newton's method with finite differences, one variable (Tables 8.1 and 8.2)
file	run0703sec.m
	Runs example 7.3 with Newton's secant method, one variable (Table 8.3)
file	run0711df.m
	Runs example 7.11 with Newton's method with finite differences (Tables 8.4 and 8.5), n variables.
file	run0711sec.m
	Runs example 7.11 with Newton's secant method (Table 8.6), n variables.
file	run0908cg.m
	Runs example 9.8 for the conjugate gradient algorithm (Table 9.1).
file	run0908quad.m
	Runs example 9.8 with the direct method (algorithm 9.1).
file	run0508.m
	Runs example 5.8 with Newton's local, n variables (Table 10.1)
file	run0508quadratic.m
	Runs example 5.8 with Newton's local with the quadratic model.
file	run0508newton.m
	Runs Newton's method with line search (Algorithm 11.8) [newtonLineSearch] on the Rosenbrock problem (Table 11.8)
file	runGoldenSection.m
	Runs example 11.3 with golden section (see goldenSection) (table 11.3)
file	runInexactLineSearch.m
	Illustrates inexact line search with example 11.1 (table 11.6)
file	runModifiedCholesky.m
	Illustrates the modified Cholesky algorithm.
file	runQuadraticInterpolation.m
	Runs example 11.3 with quadratic interpolation (table 11.2)
file	runRosenbrockNewtonLineSearch.m
	Runs Newton's method with line search (Algorithm 11.8) [newtonLineSearch] on the Rosenbrock problem.
file	runRosenbrockSteepestDescent.m
	Runs the steepest descent algorithm (Algorithm 11.6) on the Rosenbrock problem.
file	run0508tr.m
	Runs example 5.8 with Newton's method with trust region (Tables 12.1, 12.2, 12.3)
file	run1203dogleg.m
	Runs example 12.3 for the dogleg method.
file	run1203tcg.m
	Runs example 12.3 for the truncated conjugate gradients method.
file	runIntersectionTrustRegion.m
	Run to illustrate algorithm 12.1.
file	runRosenbrockTrustRegion.m
	Runs Trust region method with line search (Algorithm 12.4) [newtonTrustRegion] on the Rosenbrock problem.
file	run0508bfgs.m
	Runs example 5.8 with BFGS method with linesearch (Tables 13.1 and 13.2)
file	run0508sr1.m
	Runs example 5.8 with SR1 method with trust region (Tables 13.3 et 13.4)
file	runRosenbrockBfgs.m
	Runs BFGS with line search (Algorithm 13.1) [bfgs] on the Rosenbrock problem.
file	runRosenbrockSr1.m
	Runs Trust region method with symmetric rank one (Algorithm 13.2) [newtonTrustRegion] on the Rosenbrock problem.
file	runGaussNewton.m
	Run to illustrate the Gauss-Newton algorithm 14.1.
file	runKalman.m
	Run to illustrate the Kalman filter algorithm 14.2 (Table 14.3)
file	runNeuralNetwork.m
	Run the neural network example (Example 14.2) to illustrate the Gauss-Newton algorithm 14.1.
file	run1502nelderMead.m
	Runs example 15.2 illustrating the Nelder-Nead algorithm (Table 15.1)
file	run1503nelderMead.m
	Runs example 15.3 illustrating the Nelder-Nead algorithm (Table 15.2)
file	run1503torczon.m
	Runs example 15.3, the McKinnon example with Torczon's algorithm (Table 15.3)
file	run1604.m
	Runs example 16.4 illustrating the vertex enumeration algorithm.
file	run1604simplex.m
	Runs example 16.4 illustrating the simplex method.
file	run1607simplex.m
	Runs example 16.4 illustrating the simplex method.
file	run1612pivoting.m
	Runs example 16.12 illustrating the pivoting.
file	run1613.m
	Runs example 16.13 of [1].
file	run1615.m
	Runs example 16.15 of [1].
file	run1616.m
	Runs example 16.16 of [1].
file	runBoundConstraints.m
	Example where some combinations of basic variables are associated with a singular matrix B.
file	run1607dikin.m
	Runs example 16.7 illustrating the Dikin method (Table 17.4)
file	run1702.m
	Runs example 17.2 of [1] (Tables 17.1 and 17.2)
file	run1702constrainedNewton.m
	Runs example 17.2 of [1] with constrained Newton (Table 17.3)
file	run1703.m
	Runs example 17.3 of [1].
file	run1807longSteps.m
	Runs example 18.7 with the long steps algorithm of [1] (Table 18.7)
file	run1807predictorCorrector.m
	Runs example 18.7 with the predictor-corrector algorithm of [1] (Table 18.6)
file	run1807restrictedSteps.m
	Runs example 18.7 with the restricted steps algorithm of [1] (Table 18.5)
file	run1905.m
	Runs example 19.5 with the augmented lagrangian method of [1].
file	run1906.m
	Runs example 19.6 with the augmented lagrangian method of [1].
file	run2002.m
	Runs example 20.2 with the local SQP algorithm of [1] (Tables 20.1, 20.2, 20.3, 20.4)
file	run2003.m
	Runs example 20.3 with the local SQP algorithm of [1] (Table 20.5)
file	run2004.m
	Runs example 20.4 with the local SQP algorithm of [1] (Table 20.6)
file	run2007.m
	Runs example 20.7 with the global SQP algorithm of [1] (Tables 20.7, 20.8)
file	run2120.m
	Runs example 21.20 with the Jarnik-Prim algorithm for minimum spanning tree (Algorithm 21.4 of [1])
file	runCirculationDecomposition.m
	Run the circulation decomposition algorithm on the example represented in Figure 21.15 of [1].
file	runDivergence.m
	Calculate the divergence of the example in Figure 21.10 of [1].
file	runFlowDecomposition.m
	Run the flow decomposition algorithm on the examples represented in Figures 21.14 and 21.19 of [1].
file	runPrepareNetwork.m
	Run the function that prepares the network.
file	runSimpleCycle.m
	Run the algorithm extracting cycle flow vector on the example represented in Figure 21.15 of [1].
file	runAssignmentTrans.m
	Solve the transportation problem as a transhipment problem (Example 22.14 of [1])
file	runMaxFlowTrans.m
	Solve the max flow problem as a transhipment problem (Figure 22.6 of [1])
file	runTransportationTrans.m
	Solve the transportation problem as a transhipment problem (Example 22.12 od [1].
file	runDijkstra.m
	Run to illustrate Dijkstra's algortihm (Table 23.4)
file	runEnumeratePaths.m
	Run to illustrate the path enumeration algorithm (Table 23.1)
file	runPert.m
	Run to illustrate the use of longest path for PERT (Section 23.4 of [1].
file	runShortestPath.m
	Run to illustrate the shortest path algorithm (Table 23.2)
file	run2402.m
	Run the FordFulkerson algorithm on Example 24.2 of [1].
file	runUnsaturatedPath.m
	Run the unsaturated path algorithm on Example 24.2 of [1].
file	run2512.m
	Runs example 25.12 of [1].
file	run2702.m
	Runs example 27.2 of [1], solving the problem using an exact method.
file	run2703.m
	Runs example 27.03 of [1].
file	run2513gomory.m
	Runs example 25.13 of [1] with Algorithm 26.3.
file	run2604.m
	Runs example 26.4 of [1].
file	run2604gomory.m
	Runs example 26.4 of [1] with Algorithm 26.3.
file	runGomory.m
	Runs example of Gomory cut.
file	run2702greedy.m
	Runs example 27.2 of [1], solving the problem using the greedy heuristic.
file	run2702localSearchDeterministic.m
	Runs example 27.2 of [1], solving the problem using the local search method (Table 27.6)
file	run2702localSearchRandom.m
	Runs example 27.2 of [1], solving the problem using the local search method with random neighbors.
file	run2702simAnn.m
	Runs example 27.2 of [1], solving the problem using the simulated annealing method (see Section 27.4.1 of [1]).
file	run2702vns.m
	Runs example 27.2 of [1], solving the problem using the VNS method.
file	run2703insertion.m
	Runs example 27.3 of [1], solving the problem using the greedy heuristic (Algorithm 27.2, Table 27.2, Figure 27.4)
file	run2703localSearch.m
	Runs Algorithm 27.3 on example 27.3 of [1], solving the TSP with local search (Figure 27.11, Table 27.7, Figure 27.12)
file	run2703nearestNeighrbor.m
	Runs example 27.3 of [1], solving the problem using the greedy heuristic.
file	run2703simAnn.m
	Runs example 27.3 of [1], solving the problem using simmulated annealing (Section 27.4.2 of [1] ).
file	run2703vns.m
	Runs example 27.3 of [1], solving the problem using VNS (Section 27.3.2 of [1] ).

Detailed Description

Octave code to run the examples.