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Gurobi的Python环境配置其实为Python第三方库的安装过程
- 进入Gurobi的安装目录（含有setip.py文件）
- 文件夹目录行输入cmd，回车进入当前文件夹下命令行
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在命令行中输入 python setup.py install 回车执行即完成
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在PyCharm中尝试用Gurobi求解如下混合整数规划问题
在Gurobi安装目录下可以找到相应example文件，安装路径Gurobiwin64examplespythonmip1.py
#!/usr/bin/env python3.7
# Copyright 2021, Gurobi Optimization, LLC
# This example formulates and solves the following simple MIP model:
# maximize
# x + y + 2 z
# subject to
# x + 2 y + 3 z <= 4
# x + y >= 1
# x, y, z binary
import gurobipy as gp
from gurobipy import GRB
try:
# Create a new model
m = gp.Model("mip1")
# Create variables
x = m.addVar(vtype=GRB.BINARY, name="x")
y = m.addVar(vtype=GRB.BINARY, name="y")
z = m.addVar(vtype=GRB.BINARY, name="z")
# Set objective
m.setObjective(x + y + 2 * z, GRB.MAXIMIZE)
# Add constraint: x + 2 y + 3 z <= 4
m.addConstr(x + 2 * y + 3 * z <= 4, "c0")
# Add constraint: x + y >= 1
m.addConstr(x + y >= 1, "c1")
# Optimize model
m.optimize()
for v in m.getVars():
print('%s %g' % (v.varName, v.x))
print('Obj: %g' % m.objVal)
except gp.GurobiError as e:
print('Error code ' + str(e.errno) + ': ' + str(e))
except AttributeError:
print('Encountered an attribute error')
部分运行结果如下：
