Заболотников_9373_ПР1
.pdfЗАКЛЮЧЕНИЕ
В ходе работы были выполнены поставленные задачи и получены результаты по оптимальному решению этих задач. Также был проведён анализ чувствительности. Он показал, что если изменить цены на перевозки из первого промежуточного склада на единицу, то, в зависимости от того, цену за перевозку в какой пяти пунктов мы будем менять, изменится и значение целевой функции, однако на сам план это никак не повлияет.
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ПРИЛОЖЕНИЕ А.
КОД ПРОГРАММЫ (PYTHON)
# для первого периода
from cvxopt import matrix,solvers
c = matrix([3,4,7,4,8,2,6,6,4,3,11,12,7,10,4,12,14,8], tc = 'd') G = matrix([[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1], [0,0,-1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1]], tc = 'd')
A = matrix ([[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0], [0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,0,0,0], [0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,0,0], [0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,0], [0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1], [-1,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0], [0,-1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0]], tc = 'd')
h = matrix([60,60,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], tc = 'd')
m = matrix([160,6,26,60,10,23,0,0], tc = 'd')
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solution = solvers.lp(c, G.T, h, A.T, m, solver = 'glpk')
print('Status:', solution['status']) print('Objective:', solution['primal objective']) print('x = \n', solution['x'])
#анализ чувствительности print('analis rav,', solution['y']) print('analis rav,', solution['z'])
#для второго периода
from cvxopt import matrix,solvers
c = matrix([3,4,7,4,8,2,6,6,4,3,11,12,7,10,4,12,14,8], tc = 'd') G = matrix([[1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],
[0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0], [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1], [0,0,-1,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1]], tc = 'd')
A = matrix ([[1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], [0,0,0,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0], [0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,0,0,0],
[0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,0,0],
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[0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1,0],
[0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1], [-1,0,0,1,1,1,1,1,0,0,0,0,0,0,0,0,0,0], [0,-1,0,0,0,0,0,0,1,1,1,1,1,0,0,0,0,0]], tc = 'd')
h = matrix([60,60,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0], tc = 'd')
m = matrix([160,21,45,26,13,42,0,0], tc = 'd')
solution = solvers.lp(c, G.T, h, A.T, m, solver = 'glpk')
print('Status:', solution['status']) print('Objective:', solution['primal objective']) print('x = \n', solution['x'])
#анализ чувствительности print('analis rav,', solution['y']) print('analis rav,', solution['z'])
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