diff options
Diffstat (limited to 'ordemo')
| -rw-r--r-- | ordemo/lp_mip.py | 38 |
1 files changed, 38 insertions, 0 deletions
diff --git a/ordemo/lp_mip.py b/ordemo/lp_mip.py new file mode 100644 index 0000000..f135523 --- /dev/null +++ b/ordemo/lp_mip.py @@ -0,0 +1,38 @@ +from ortools.linear_solver import pywraplp +import numpy as np + + +# solver = pywraplp.Solver('Maximize army power', pywraplp.Solver.GLOP_LINEAR_PROGRAMMING) +# solver = pywraplp.Solver('Maximize army power', pywraplp.Solver.GLPK_LINEAR_PROGRAMMING) +# solver = pywraplp.Solver('Maximize army power', pywraplp.Solver.CLP_LINEAR_PROGRAMMING) +solver = pywraplp.Solver('Maximize army power', pywraplp.Solver.CBC_MIXED_INTEGER_PROGRAMMING) + + +swordsmen = solver.IntVar(0, solver.infinity(), 'swordsmen') +bowmen = solver.IntVar(0, solver.infinity(), 'bowmen') +horsemen = solver.IntVar(0, solver.infinity(), 'horsemen') + +x = np.asarray([swordsmen, bowmen, horsemen]) +A = np.asarray([[60, 20, 0], [80, 10, 40], [140, 0, 100]]) +b = np.asarray([1200, 800, 600]) +c = np.asarray([70, 95, 230]) + +Ax = A.T.dot(x) +for i in range(len(b)): + solver.Add(Ax[i] <= b[i]) + +solver.Maximize(np.inner(x, c)) + +status = solver.Solve() +# If an optimal solution has been found, print results +if status == pywraplp.Solver.OPTIMAL: + print('================= Solution =================') + print(f'Solved in {solver.wall_time():.2f} milliseconds in {solver.iterations()} iterations') + print() + print(f'Optimal power = {solver.Objective().Value()} 💪power') + print('Army:') + print(f' - 🗡️Swordsmen = {swordsmen.solution_value()}') + print(f' - 🏹Bowmen = {bowmen.solution_value()}') + print(f' - 🐎Horsemen = {horsemen.solution_value()}') +else: + print('The solver could not find an optimal solution.')
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