将CPLEX数学模型从C ++传输到Python [英] transfer CPLEX mathematical model from C++ to Python

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本文介绍了将CPLEX数学模型从C ++传输到Python的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我已经使用CPLEX在C ++中对我的数学模型进行了编程,现在我想使用docplex.mp.model将其转移到Python中我在添加约束时遇到了一些问题.在C ++中,我习惯于添加这样的约束

I have programmed my mathematical model in C++ using CPLEX,now I want to transfer it to Python using docplex.mp.model I met some problems in adding constraints. In C++,I am used to add constraints like this

for (j = NumD; j < NumDC; j++)
{
    IloExpr v(env);
    for (i = 0; i < NumDC; i++)
    {
        for (k = 0; k < NumV; k++)
        {
            v += xijk[i][j][k];
        }
    }
    model.add(v >= 1);
}

我是这样用python编写这段代码的:

I write this code in python like this:

for j in range(NumD,NumDC):
    v = model.linear_expr()
    for i in range(NumDC):
        for k in range(NumV):
            v+=xijk[i,j,k]
    model.add_constraint(v >= 1)

这是对的吗?谢谢:)

推荐答案

您可以使用python sum甚至model.sum

You could use python sum or even model.sum

参见示例

https://github.com/AlexFleischerParis/zoodocplex/blob/master/zoodatainalistoftuple.py

from docplex.mp.model import Model

# Data

Buses=[
    (40,500),
    (30,400)
    ]

nbKids=300

# Indexes

busSize=0;
busCost=1;

for b in Buses:
    print("buses with ",b[busSize]," seats cost ",b[busCost])

mdl = Model(name='buses')

#decision variables
mdl.nbBus=mdl.integer_var_dict(Buses,name="nbBus")

# Constraint
mdl.add_constraint(mdl.sum(mdl.nbBus[b]*b[busSize] for b in Buses) >= nbKids, 'kids')

# Objective
mdl.minimize(mdl.sum(mdl.nbBus[b]*b[busCost] for b in Buses))

mdl.solve()

# Display solution
for b in Buses:
    print(mdl.nbBus[b].solution_value," buses with ",b[busSize]," seats"); 

"""
which gives
buses with  40  seats cost  500
buses with  30  seats cost  400
6.0  buses with  40  seats
2.0  buses with  30  seats
"""

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