Examples

Initialize HiGHS

HiGHS must be initialized before making calls to the HiGHS Python library, and the examples below assume that it has been done

import highspy
import numpy as np
h = highspy.Highs()

Read a model

To read a model into HiGHS from a MPS files and (CPLEX) LP files pass the file name to readModel.

# Read a model from MPS file model.mps
filename = 'model.mps'
status = h.readModel(filename)
print('Reading model file ', filename, ' returns a status of ', status)
filename = 'model.dat'
status = h.readModel(filename)
print('Reading model file ', filename, ' returns a status of ', status)

Build a model

Build the model

minimize    f  =  x0 +  x1
subject to              x1 <= 7
            5 <=  x0 + 2x1 <= 15
            6 <= 3x0 + 2x1
            0 <= x0 <= 4; 1 <= x1

Using the simplified interface, the model can be built as follows:

x0 = h.addVar(lb = 0, ub = 4)
x1 = h.addVar(lb = 1, ub = 7)

h.addConstr(5 <=   x0 + 2*x1 <= 15)
h.addConstr(6 <= 3*x0 + 2*x1)

h.minimize(x0 + x1)

Alternatively, the model can be built using the more general interface, which allows the user to specify the model in a more flexible way.

Firstly, one variable at a time, via a sequence of calls to addVar and addRow:s

inf = highspy.kHighsInf
# Define two variables, first using identifiers for the bound values,
# and then using constants
lower = 0
upper = 4
h.addVar(lower, upper)
h.addVar(1, inf)

# Define the objective coefficients (costs) of the two variables,
# identifying the variable by index, and changing its cost from the
# default value of zero
cost = 1
h.changeColCost(0, cost)
h.changeColCost(1, 1)

# Define constraints for the model
#
# The first constraint (x1<=7) has only one nonzero coefficient,
# identified by variable index 1 and value 1
num_nz = 1
index = 1
value = 1
h.addRow(-inf, 7, num_nz, index, value)

# The second constraint (5 <= x0 + 2x1 <= 15) has two nonzero
# coefficients, so arrays of indices and values are required
num_nz = 2
index = np.array([0, 1])
value = np.array([1, 2])
h.addRow(5, 15, num_nz, index, value)

# The final constraint (6 <= 3x0 + 2x1) has the same indices but
# different values
num_nz = 2
value = np.array([3, 2])
h.addRow(6, inf, num_nz, index, value)

# Access LP
lp = h.getLp()
num_nz = h.getNumNz()
print('LP has ', lp.num_col_, ' columns', lp.num_row_, ' rows and ', num_nz, ' nonzeros')

Alternatively, via calls to addCols and addRows.

inf = highspy.kHighsInf
# The constraint matrix is defined with the rows below, but parameters
# for an empty (column-wise) matrix must be passed
cost = np.array([1, 1], dtype=np.double)
lower = np.array([0, 1], dtype=np.double)
upper = np.array([4, inf], dtype=np.double)
num_nz = 0
start = 0
index = 0
value = 0
h.addCols(2, cost, lower, upper, num_nz, start, index, value)
# Add the rows, with the constraint matrix row-wise
lower = np.array([-inf, 5, 6], dtype=np.double)
upper = np.array([7, 15, inf], dtype=np.double)
num_nz = 5
start = np.array([0, 1, 3])
index = np.array([1, 0, 1, 0, 1])
value = np.array([1, 1, 2, 3, 2], dtype=np.double)
h.addRows(3, lower, upper, num_nz, start, index, value)

passColName
passRowName

Pass a model

Pass a model from a HighsLp instance

inf = highspy.kHighsInf
# Define a HighsLp instance
lp = highspy.HighsLp()
lp.num_col_ = 2;
lp.num_row_ = 3;
lp.col_cost_ = np.array([1, 1], dtype=np.double)
lp.col_lower_ = np.array([0, 1], dtype=np.double)
lp.col_upper_ = np.array([4, inf], dtype=np.double)
lp.row_lower_ = np.array([-inf, 5, 6], dtype=np.double)
lp.row_upper_ = np.array([7, 15, inf], dtype=np.double)
# In a HighsLp instsance, the number of nonzeros is given by a fictitious final start
lp.a_matrix_.start_ = np.array([0, 2, 5])
lp.a_matrix_.index_ = np.array([1, 2, 0, 1, 2])
lp.a_matrix_.value_ = np.array([1, 3, 1, 2, 2], dtype=np.double)
h.passModel(lp)

Solve the model

The incumbent model in HiGHS is solved by calling

h.run()

Print solution information

solution = h.getSolution()
basis = h.getBasis()
info = h.getInfo()
model_status = h.getModelStatus()
print('Model status = ', h.modelStatusToString(model_status))
print()
print('Optimal objective = ', info.objective_function_value)
print('Iteration count = ', info.simplex_iteration_count)
print('Primal solution status = ', h.solutionStatusToString(info.primal_solution_status))
print('Dual solution status = ', h.solutionStatusToString(info.dual_solution_status))
print('Basis validity = ', h.basisValidityToString(info.basis_validity))