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Imports System
Imports System.Diagnostics
Imports CenterSpace.NMath.Core
Namespace CenterSpace.NMath.Examples.VisualBasic
A .NET example in Visual Basic showing how to use the stochastic hill
climbing solver <c>StochasticHillClimbingSolver</c> to solve a
nonlinear programming problem.
W. Hock, K. Schittkowski, Test Examples for Nonlinear Programming Codes.
This is problem number 86.
Public Module StochasticHillClimbingExample
Sub Main()
Create the objective function as an instance of a class derived from
DoubleFunctional.
Dim F As New ObjectiveFunction()
Construct the nonlinear programming problem. There are
five constraints and each variable is required to be >= 0.
Dim Problem As New NonlinearProgrammingProblem(F)
Dim NumVars As Integer = 5
Dim NumConstraints As Integer = 10
Dim I As Integer = 0
For I = 0 To NumConstraints - 1
Value of the ith constraint function must be >= 0.
Problem.AddLowerBoundConstraint(New ConstraintFunctions(I), 0.0)
Next
For I = 0 To NumVars - 1
Each variable must be >= 0.
Problem.AddLowerBound(I, 0.0)
Next
Create the solver object.
Dim Solver As New StochasticHillClimbingSolver()
The solver is stochastic. Setting a random seed before
the solver will ensure consistent results between runs.
Solver.RandomSeed = &H248
Create a solver parameter object and set a time limit for
the solver. By default the solver will run until a solution
is found. Since this could take forever, it is a good idea to
set a reasonable time limit on the solve. Here we set the time
limit for ten seconds. If an optimal solution is not found within
the specified time limit the solver will exit and the solvers
Result property will be equal to SolverResult.SolverInterrupted.
We also specify that we want to presolve. By default there is no
presolve step. For some problems presolve can reduce the size and
complexity and result in fewer steps to reach a solution.
Dim SolverParams As New StochasticHillClimbingParameters
SolverParams.TimeLimitMilliSeconds = 10000
SolverParams.Presolve = True
Attempt the solver and write out the results.
Solver.Solve(Problem, SolverParams)
Console.WriteLine("Solver Result = " & Solver.Result)
Console.WriteLine("Number of steps = " & Solver.Steps)
Console.WriteLine("Optimal x = " & Solver.OptimalX.ToString("F3"))
Console.WriteLine("Optimal function value = " & Solver.OptimalObjectiveFunctionValue.ToString("F3"))
Console.WriteLine()
Console.WriteLine("Press Enter Key")
Console.Read()
End Sub
Objective function. This is the function we want to minimize.
Private Class ObjectiveFunction
Inherits DoubleFunctional
Constants used in evaluating the objective function.
Private C_ As DoubleSymmetricMatrix
Private D_ As DoubleVector
Private E_ As DoubleVector
Constructs an instance of the objective function.
Sub New()
MyBase.New(5)
E_ = New DoubleVector(-15.0, -27.0, -36.0, -18.0, -12.0)
D_ = New DoubleVector(4.0, 8.0, 10.0, 6.0, 2.0)
C_ = New DoubleSymmetricMatrix(5)
C_(0, 0) = 30
C_(0, 1) = -20
C_(0, 2) = -10
C_(0, 3) = 32
C_(0, 4) = -10
C_(1, 1) = 39
C_(1, 2) = -6
C_(1, 3) = -31
C_(1, 4) = 32
C_(2, 2) = 10
C_(2, 3) = -6
C_(2, 4) = -10
C_(3, 3) = 39
C_(3, 4) = -20
C_(4, 4) = 30
End Sub
Evaluates the objective function at the given point.
<param name="x">Evaluate at this point.</param>
<returns>The objective function value at the point.</returns>
Public Overrides Function Evaluate(X As DoubleVector) As Double
Dim S1 As Double = 0
Dim S2 As Double = 0
Dim S3 As Double = 0
Dim I As Integer
For I = 0 To 4
S1 = S1 + E_(I) * X(I)
Dim J As Integer
For J = 0 To 4
S2 = S2 + C_(I, J) * X(I) * X(J)
Next
S3 = S3 + D_(I) * Math.Pow(X(I), 3)
Next
Return S1 + S2 + S3
End Function
End Class
<summary>
Constraint functions for the nonlinear programming problem.
Constraints contain five variables. Ten different constraint
objects may be constructed.
</summary>
Class ConstraintFunctions
Inherits DoubleFunctional
<summary>
Coefficients for each of the ten different constraints.
Each row of the matrix contains coefficients for the five
variables.
</summary>
Private Shared AData As DoubleMatrix
<summary>
Constant values used in evaluating each of the ten different
constraints.
</summary>
Private Shared BData As DoubleVector
<summary>
References the variable coefficients for this constraint.
</summary>
Private ARow As DoubleVector
<summary>
The constant value for this constraint.
</summary>
Private BValue As Double
Shared Sub New()
Dim ADataArray(,) As Double = New Double(,) {{-16.0, 2.0, 0.0, 1.0, 0.0}, {0.0, -2.0, 0.0, 0.4, 2.0},
{-3.5, 0, 2, 0, 0},
{0, -2, 0, -4, -1},
{0, -9, -2, 1, -2.8},
{2, 0, -4, 0, 0},
{-1, -1, -1, -1, -1},
{-1, -2, -3, -2, -1},
{1, 2, 3, 4, 5},
{1, 1, 1, 1, 1}
}
AData = New DoubleMatrix(ADataArray)
BData = New DoubleVector(-40.0, -2.0, -0.25, -4, -4, -1, -40, -60, 5, 1)
End Sub
<summary>
Constructs an instance of one of the ten constraint functions.
</summary>
<param name="i">Constraint function number. Must be between
0 and 9 inclusive.</param>
<exception cref="InvalidArgumentException">Thrown if the constraint
number is less than zero or greater than 9.</exception>
Public Sub New(I As Integer)
MyBase.New(5)
If (I < 0 Or I > AData.Rows) Then
Dim Msg = String.Format("Invalid constraint number {0}. Must be between 0 and 9", I)
Throw New InvalidArgumentException(Msg)
End If
ARow = AData.Row(I)
BValue = BData(I)
End Sub
<summary>
Evaluates the constraint function at the given point.
</summary>
<param name="x">Point to evaluate at.</param>
<returns>Constraint value at the given point.</returns>
Public Overrides Function Evaluate(X As DoubleVector) As Double
Return NMathFunctions.Dot(ARow, X) - BValue
End Function
End Class
End Module
End Namespace
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