我如何为优化数学编程（MIP）制定这些约束
我正在努力解决一些范围范围的变量和几个决策变量的约束。
限制是
`if a[i] <= t <= a[i]+b[i], then M[t][i] == 1,
else if t < a[i] or t > a[i]+b[i], then M[t][i] == 0.
decision variables (int a[i], b[i])
(boolean M[t][i])
Examples of ranges of the variables
0 <= a[i] <= 50
0 <= b[i] <= 10
0 <= t <= 100`
我想将这些配方（例如大-M方法或等等）线性化...
PLZ，让我知道克服它的方法。 谢谢。
通过使用Big-M方法或等等的线性化...
例如...
M*t + (M-1)*t <= M*(a[i]) + (M-1)*a[i]
I am struggling with some constraints that have ranged variables and several decision variables.
The constraints are
`if a[i] <= t <= a[i]+b[i], then M[t][i] == 1,
else if t < a[i] or t > a[i]+b[i], then M[t][i] == 0.
decision variables (int a[i], b[i])
(boolean M[t][i])
Examples of ranges of the variables
0 <= a[i] <= 50
0 <= b[i] <= 10
0 <= t <= 100`
I'd like to linearize these formulations, like as Big-M method or etc...
Plz, let me know the way to overcome it.
Thank you.
Linearization by using the Big-M method or etc...
such as...
M*t + (M-1)*t <= M*(a[i]) + (M-1)*a[i]
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