[英]How to Convert Quadratic Contraint to Linear
I have this constraint in my model:我的 model 中有这个约束:
(X - Y) @ B >= 0
where B is a boolean vector variable, X and Y are variables vector that represent quantities其中 B 是 boolean 向量变量,X 和 Y 是表示数量的变量向量
I'm working with CVXPY, so I have to keep linear expressions我正在使用 CVXPY,所以我必须保持线性表达式
How could I translate this constraint in a way that is linear?我怎样才能以线性的方式翻译这个约束?
Could someone help me please?有人可以帮我吗?
I am assuming that X>=0
and Y>=0
.我假设
X>=0
和Y>=0
。 In that case, we can somewhat easily linearize XB=X*B
and YB=Y*B
.在这种情况下,我们可以稍微轻松地线性化
XB=X*B
和YB=Y*B
。
XB <= X
XB <= B*999
XB >= X-999*(1-B)
0 <= XB <= 999
Here 999 is an upper bound on X
.这里 999 是
X
的上限。 Similar for YB
. YB
类似。 Now just add:现在只需添加:
XB >= YB
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