LSCP-B

notebooks/lscp.ipynb

@@ -906,10 +906,10 @@
  ],
  "metadata": {
   "interpreter": {
-   "hash": "31b88bb145573cdebdaa7fd72fef7949ecb3dda26d5e10d4ccc660a5d07787a7"
+   "hash": "56b72aab97c5d88c22a6bf5872989e2e65e9296dc12395fbfb8350007c775deb"
   },
   "kernelspec": {
-   "display_name": "Python 3.9.9 ('spopt')",
+   "display_name": "Python 3.8.13 ('geo_env')",
    "language": "python",
    "name": "python3"
   },
@@ -923,7 +923,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.9"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,

spopt/locate/__init__.py

@@ -1,5 +1,5 @@
 from .base import BaseOutputMixin, CoveragePercentageMixin, MeanDistanceMixin
-from .coverage import LSCP, MCLP
+from .coverage import LSCP, MCLP, LSCPB
 from .p_median import PMedian
 from .p_center import PCenter
 from .util import simulated_geo_points

spopt/locate/base.py

@@ -75,7 +75,10 @@ def client_facility_array(self) -> None:
                 for fac_site in self.fac2cli[i]:
                     self.cli2fac[fac_site].append(i)
         else:
-            raise AttributeError("The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute")
+            raise AttributeError(
+                "The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute"
+            )
+
 
 class CoveragePercentageMixin:
     """
@@ -103,8 +106,9 @@ def uncovered_clients(self) -> None:
 
             self.n_cli_uncov = self.aij.shape[0] - len(set_cov)
         else:
-            raise AttributeError("The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute")
-
+            raise AttributeError(
+                "The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute"
+            )
 
     def get_percentage(self):
         """
@@ -113,7 +117,10 @@ def get_percentage(self):
         if hasattr(self, "n_cli_uncov"):
             self.percentage = 1 - (self.n_cli_uncov / self.aij.shape[0])
         else:
-            raise AttributeError("The attribute `n_cli_uncov` is not set. See `uncovered_clients` method to set the attribute.")
+            raise AttributeError(
+                "The attribute `n_cli_uncov` is not set. See `uncovered_clients` method to set the attribute."
+            )
+
 
 class MeanDistanceMixin:
     """
@@ -291,6 +298,59 @@ def add_set_covering_constraint(
                 "before setting constraints must set facility variable"
             )
 
+    @staticmethod
+    def add_backup_covering_constraint(
+        obj: T_FacModel,
+        model: pulp.LpProblem,
+        ni: np.array,
+        range_facility: range,
+        range_client: range,
+    ) -> None:
+        """
+        backup covering constraint:
+        - coverage_0 + facility_1 + facility_3 + facility_4 + facility_6 + facility_7 + facility_9 >= 1
+
+        Parameters
+        ----------
+        obj: T_FacModel
+            bounded type of LocateSolver class
+        model: pulp.LpProblem
+            optimization model problem
+        ni: np.array
+            two-dimensional array that defines candidate sites between facility points within a distance to supply {i}
+            demand point
+        range_facility: range
+            range of facility points quantity
+        range_client: range
+            range of demand points quantity
+        Returns
+        -------
+        None
+
+        """
+        if hasattr(obj, "fac_vars"):
+            fac_vars = getattr(obj, "fac_vars")
+            cli_vars = getattr(obj, "cli_vars")
+            for i in range_client:
+                if sum(ni[i]) >= 2:
+                    model += (
+                        pulp.lpSum(
+                            [int(ni[i][j]) * fac_vars[j] for j in range_facility]
+                        )
+                        >= 1 + 1 * cli_vars[i]
+                    )
+                else:
+                    model += (
+                        pulp.lpSum(
+                            [int(ni[i][j]) * fac_vars[j] for j in range_facility]
+                        )
+                        >= 1 + 0 * cli_vars[i]
+                    )
+        else:
+            raise AttributeError(
+                "before setting constraints must set facility variable"
+            )
+
     @staticmethod
     def add_facility_constraint(
         obj: T_FacModel, model: pulp.LpProblem, p_facilities: int