X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/LiCO.git/blobdiff_plain/6218ab50f32a9fd3c09d40b9196ce96128536e11..a46087d6b626d4b027a6df8254829981f14e602d:/PeCO-EO/articleeo.tex?ds=sidebyside

diff --git a/PeCO-EO/articleeo.tex b/PeCO-EO/articleeo.tex
index a80c51c..0927d21 100644
--- a/PeCO-EO/articleeo.tex
+++ b/PeCO-EO/articleeo.tex
@@ -532,9 +532,10 @@ Our coverage optimization problem can then be mathematically expressed as follow
 \begin{array}{ll}
 \min \sum_{j \in S} \sum_{i \in I_j} (\alpha^j_i ~ M^j_i + \beta^j_i ~ V^j_i )&\\
 \textrm{subject to :}&\\
-\sum_{k \in A} ( a^j_{ik} ~ X_{k}) + M^j_i  = l \quad \forall i \in I_j, \forall j \in S\\
-\sum_{k \in A} ( a^j_{ik} ~ X_{k}) - V^j_i  = l \quad \forall i \in I_j, \forall j \in S\\
+\sum_{k \in A} ( a^j_{ik} ~ X_{k}) + M^j_i  \geq l \quad \forall i \in I_j, \forall j \in S\\
+\sum_{k \in A} ( a^j_{ik} ~ X_{k}) - V^j_i  \leq l \quad \forall i \in I_j, \forall j \in S\\
 X_{k} \in \{0,1\}, \forall k \in A
+M^j_i, V^j_i \in  \mathbb{R}^{+}
 \end{array}
 \right.
 \end{equation}