@@ 22,16 22,16 @@ Enbo Zhou.
> Mathematical programming usually has the following form:
>
-> Maximize/Minimize f(X_1_, X_2_, ... x_n_)
+> Maximize/Minimize f(X_1, X_2, ... x_n)
>
-> Subject to g_1_(X_1_, X_2_, ... x_n_) <= b_1_; g_2_(X_1_, X_2_, ... x_n_) <= b_2_; ... g_m_(X_1_, X_2_, ... x_n_) <= b_m_
+> Subject to g_1(X_1, X_2, ... x_n) <= b_1; g_2(X_1, X_2, ... x_n) <= b_2; ... g_m(X_1, X_2, ... x_n) <= b_m
>
-> Where X_i_, i = 1, 2, ... n, are decision variables,
+> Where X_i, i = 1, 2, ... n, are decision variables,
> f is the objective function measuring soluton quality,
> and we optimize f to acquire the best solution.
-> g_i_, i = 1, 2, ... m, are mathmatical [functions] to help formalize
+> g_i, i = 1, 2, ... m, are mathmatical [functions] to help formalize
> constraints.
-> b_i_, i = 1, 2, ... m are constants to define constraints.
+> b_i, i = 1, 2, ... m are constants to define constraints.
> [L]et us assume that that the US Forest Service is planning to treat 100
> acres (threshold capacity) of the Stanislaus National Forest to decrease