added LP structure

modelling/scheduler.py

@@ -0,0 +1,64 @@
+import pandas as pd
+import numpy as np
+import pyomo.environ as pe
+import pyomo.gdp as pyogdp
+from pyomo.core.base.set_types import Any
+
+
+# check with Taha if code is too similar to Alstom?
+class TheatreScheduler:
+
+    def __init__(self):
+        pass
+
+    def _generate_cases(self):
+        pass
+
+    def create_model(self):
+        model = pe.ConcreteModel()
+
+        # Model Data
+        model.CASES = pe.Set()  # indexed by (caseID, sessionID)
+        model.CASE_DURATIONS = pe.Param()  # median case times
+        model.SESSION_DURATIONS = pe.param()  # session durations
+        model.M = pe.Param()  # big M
+        max_util = 0.85
+
+        # Decision Variables
+        model.SESSION_ASSIGNED = pe.Var()
+        model.CASE_START_TIME = pe.Var()
+        model.UTILISATION = pe.Var()
+
+        # Objective
+        def objective_function(model):
+            pass
+        model.OBJECTIVE = pe.Objective()
+
+        # Constraints
+        # Case start time must be after start time of assigned theatre session
+        def case_start_time():
+            pass
+        model.CASE_START = pe.Constraint()
+
+        # Case end time must be before end time of assigned theatre session
+        def case_end_time():
+            pass
+        model.CASE_END_TIME = pe.Constraint()
+
+        # Cases can be assigned to a maximum of one session
+        def session_assignment():
+            pass
+        model.SESSION_ASSIGNMENT = pe.Constraint()
+
+        def disjunctions():
+            pass
+        model.DISJUNCTIONS = pyogdp.Disjunction()
+
+        def theatre_util():
+            pass
+        model.THEATRE_UTIL = pe.Constraint()
+
+        return model
+
+    def solve(self):
+        pass