import com.lindo.*;
public class ex_modify extends Lindo{
/* ex_modify.java
A Java programming example of interfacing with the
LINDO API demonstrating
1) Adding new variables and constraints.
2) Modifying objective coefficients
Original problem:
MAX = 20 * A + 30 * C
S.T. A + 2 * C <= 120
A <= 60
C <= 50
Modified problem after adding a variable:
MAX = 20 * A + 30 * C - 2 *D
S.T. A + 2 * C <= 120
A <= 60
C <= 50
Modified problem after adding a constraint:
MAX = 20 * A + 30 * C - 2 *D
S.T. A + 2 * C <= 120
A <= 60
C <= 50
[ C + D >= 50] (*)
Modified problem after changing objective
coefficients.
MAX= -10 * A + 30 * C - 3 *D
S.T. A + 2 * C <= 120
A <= 60
C <= 50
C + D >= 50
Solving such a problem with the LINDO API involves
the following steps:
1. Create a LINDO environment.
2. Create a model in the environment.
3. Specify the model.
4a. Add a new variable
4b. Add a new constraint
4c. Modify obj coeff
5. Perform the optimization.
6. Retrieve the solution.
7. Delete the LINDO environement.
*/
private static int nErrorCode[] = new int[1];
private static StringBuffer cErrorMessage = new StringBuffer();
private static StringBuffer cLicenseKey = new StringBuffer();
double[][] array = null;
double[] adC = null;
double[] adB = null;
private static int[] pEnv = new int[3];
private static int pModel[] = new int[3];
private static int[] pEnvCopy = new int[3];
private static Object[] a = null;
/* Number of constraints, Number of variables */static int nM = 0, nN = 0;
/* The length of each column. Since we aren't leaving any blanks in our matrix, we can set this to null */
static int pnLenCol[] = null;
/* The nonzero coefficients */static double adA[] = null;
/* The row indices of the nonzero coefficients */static int anRowX[] = null;
/* Simple upper and lower bounds on the variables.
By default, all variables have a lower bound of zero
and an upper bound of infinity. Therefore pass null
pointers in order to use these default values. */
static double pdLower[] = null, pdUpper[] = null;
/* The number of nonzeros in the constraint matrix */static int nNZ = 0;
/* The indices of the first nonzero in each column */static int anBegCol[] = null;
/* The length of each column. Since there are no balnks can be null */static int[]
Alencol = null;
/* LB and UB of the variable, null means 0 LB and infinity UB */static double[]
lb = null, ub = null;
static String varnames[] = null, connames[] = null;
static {
// The runtime system executes a class's static
// initializer when it loads the class.
System.loadLibrary("lindojni");
nErrorCode[0] = LSloadLicenseString("d:/lindoapi/license/license.h", cLicenseKey);
APIErrorCheck(pEnv);
pEnv[0] = LScreateEnv(nErrorCode, cLicenseKey.toString());
APIErrorCheck(pEnv);
pEnvCopy[0] = pEnv[0];
pModel[0] = LScreateModel(pEnv[0], nErrorCode);
}
// Generalized error Reporting function
private static void APIErrorCheck(int pEnv[]) {
if (0 != nErrorCode[0]) {
LSgetErrorMessage(pEnv[0], nErrorCode[0], cErrorMessage);
System.out.println("\nError " + nErrorCode[0] + ": " + cErrorMessage);
System.out.println();
System.exit(1);
}
}
public static void main(String[] argv)
{
/* Number of constraints */
int nM = 3;
/* Number of variables */
int nN = 2;
/* >>> Step 3 <<< Specify the model.
To specify our model, we make a call to LSloadLPData,
passing it:
- A pointer to the model which we are specifying(pModel)
- The number of constraints in the model
- The number of variables in the model
- The direction of the optimization (i.e. minimize or
- maximize)
- The value of the constant term in the objective (may
be zero)
- The coefficients of the objective function
- The right-hand sides of the constraints
- The types of the constraints
- The number of nonzeros in the constraint matrix
- The indices of the first nonzero in each column
- The length of each column
- The nonzero coefficients
- The row indices of the nonzero coefficients
- Simple upper and lower bounds on the variables
*/
/* The direction of optimization */
int nDir = LS_MAX;
/* The objective's constant term */
double dObjConst = 0.;
/* The coefficients of the objective function */
double adC[] = new double[] { 20., 30.};
/* The right-hand sides of the constraints */
double adB[] = new double[] { 120., 60., 50.};
/* The constraint types */
String acConTypes = "LLL";
/* The number of nonzeros in the constraint matrix */
int nNZ = 4;
/* The indices of the first nonzero in each column */
int anBegCol[] = new int[] { 0, 2, nNZ};
/* The length of each column. Since we aren't leaving
any blanks in our matrix, we can set this to null */
int pnLenCol[] = null;
/* The nonzero coefficients */
double adA[] = new double[]{ 1., 1., 2., 1.};
/* The row indices of the nonzero coefficients */
int anRowX[] = new int[] { 0, 1, 0, 2};
/* Simple upper and lower bounds on the variables.
By default, all variables have a lower bound of zero
and an upper bound of infinity. Therefore pass null
pointers in order to use these default values. */
double pdLower[] = null, pdUpper[] = null;
/* We have now assembled a full description of the model.
We pass this information to LSloadLPData with the
following call. */
nErrorCode[0] = LSloadLPData(pModel[0], nM, nN, nDir,
dObjConst, adC, adB, acConTypes, nNZ, anBegCol,
pnLenCol, adA, anRowX, pdLower, pdUpper);
APIErrorCheck(pEnv);
nErrorCode[0] = LSwriteLINDOFile(pModel[0],"original.ltx");
APIErrorCheck(pEnv);
/* >>> Step 4.c <<< Modify coeff of variables */
int i;
double padC [] = new double[2];
int paiVars[] = new int[2];
/* indices of the variables to be modified */
paiVars[0] = 0;
paiVars[1] = 1;
/* new obj coefficients of these variables */
padC[0] = -10;
padC[1] = -3;
nErrorCode[0] = LSmodifyObjective(pModel[0],2, paiVars, padC);
APIErrorCheck(pEnv);
nErrorCode[0] = LSwriteLINDOFile(pModel[0],"modified-1.ltx");
APIErrorCheck(pEnv);
String acNewConTypes = "EE";
int paiCons[] = new int[2];
/* indices of the variables to be modified */
paiCons[0] = 0;
paiCons[1] = 1;
nErrorCode[0] = LSmodifyConstraintType(pModel[0],2, paiCons, acNewConTypes);
APIErrorCheck(pEnv);
nErrorCode[0] = LSwriteLINDOFile(pModel[0],"modified-2.ltx");
APIErrorCheck(pEnv);
}
{
/* >>> Step 6 <<< Retrieve the solution */
int i;
double adX[] = new double[100], dObj[]= new double[1];
double adDec[] = new double[100], adInc[]= new double[100];
/* >>> Step 5 <<< Perform the optimization */
nErrorCode[0] = LSoptimize( pModel[0], LS_METHOD_PSIMPLEX, null);
APIErrorCheck(pEnv);
/* Get the value of the objective */
nErrorCode[0] = LSgetInfo(pModel[0],LS_DINFO_POBJ, dObj);
APIErrorCheck(pEnv);
System.out.println( "Objective Value =\n"+dObj);
/* Get the variable values */
nErrorCode[0] = LSgetPrimalSolution ( pModel[0], adX);
APIErrorCheck(pEnv);
int[] nVar = new int[1];
nErrorCode[0] = LSgetInfo ( pModel[0], LS_IINFO_NUM_VARS, nVar);
System.out.println("Primal values = ");
for (i = 0; i < nN; i++) System.out.println( "%g "+adX[i]);
System.out.println("\n");
/* >>> Step 7 <<< Delete the LINDO environment */
nErrorCode[0] = LSdeleteEnv( pEnv);
}
}
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