Add deactivatePricer

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 ## Unreleased
 ### Added
+- Wrapper SCIPdeactivatePricer and added deactivatePricer and test
 - Added getLinearConsIndicator
 - Added SCIP_LPPARAM, setIntParam, setRealParam, getIntParam, getRealParam, isOptimal, getObjVal, getRedcost for lpi
 - Added isFeasPositive

src/pyscipopt/scip.pxd

@@ -998,6 +998,7 @@ cdef extern from "scip/scip.h":
                                    SCIP_PRICERDATA* pricerdata)
     SCIP_PRICER* SCIPfindPricer(SCIP* scip, const char* name)
     SCIP_RETCODE SCIPactivatePricer(SCIP* scip, SCIP_PRICER* pricer)
+    SCIP_RETCODE SCIPdeactivatePricer(SCIP* scip, SCIP_PRICER* pricer)
     SCIP_PRICERDATA* SCIPpricerGetData(SCIP_PRICER* pricer)
 
     # Constraint handler plugin

src/pyscipopt/scip.pxi

@@ -298,7 +298,7 @@
     if rc == SCIP_OKAY:
         pass
     elif rc == SCIP_ERROR:
         raise Exception('SCIP: unspecified error!')
     elif rc == SCIP_NOMEMORY:
         raise MemoryError('SCIP: insufficient memory error!')
     elif rc == SCIP_READERROR:
@@ -7593,6 +7593,7 @@
         PY_SCIP_CALL(SCIPactivatePricer(self._scip, scip_pricer))
         pricer.model = <Model>weakref.proxy(self)
         Py_INCREF(pricer)
+        pricer._name = name
 
     def includeConshdlr(self, Conshdlr conshdlr, name, desc, sepapriority=0,
                         enfopriority=0, chckpriority=0, sepafreq=-1, propfreq=-1,
@@ -7654,6 +7655,19 @@
         conshdlr.name = name
         Py_INCREF(conshdlr)
 
+    def deactivatePricer(self, Pricer pricer):
+        """
+        Deactivate the given pricer.
+
+        Parameters
+        ----------
+        pricer : Pricer
+            the pricer to deactivate
+        """
+        cdef SCIP_PRICER* scip_pricer
+        scip_pricer = SCIPfindPricer(self._scip, str_conversion(pricer._name))
+        PY_SCIP_CALL(SCIPdeactivatePricer(self._scip, scip_pricer))
+
     def copyLargeNeighborhoodSearch(self, to_fix, fix_vals) -> Model:
         """
         Creates a configured copy of the transformed problem and applies provided fixings intended for LNS heuristics.

tests/test_pricer.py

@@ -67,6 +67,10 @@ def pricerredcost(self):
             self.data['patterns'].append(newPattern)
             self.data['var'].append(newVar)
 
+        if self.data["deactivate"]:
+            # Testing deactivatePricer
+            self.model.deactivatePricer(self)
+
         return {'result':SCIP_RESULT.SUCCESS}
 
     # The initialisation function for the variable pricer to retrieve the transformed constraints of the problem
@@ -124,6 +128,7 @@ def test_cuttingstock():
     pricer.data['rollLength'] = rollLength
     pricer.data['patterns'] = patterns
     pricer.data['redcosts'] = []
+    pricer.data["deactivate"] = False
 
     # solve problem
     s.optimize()
@@ -174,4 +179,61 @@ class IncompletePricer(Pricer):
     model.includePricer(pricer, "", "") 
 
     with pytest.raises(Exception):
-        model.optimize()
+        model.optimize()
+
+def test_deactivate_pricer():
+    # create solver instance
+    s = Model("CuttingStock")
+
+    s.setPresolve(0)
+    s.data = {}
+    s.data["nSols"] = 0
+
+    # creating a pricer
+    pricer = CutPricer()
+    s.includePricer(pricer, "CuttingStockPricer", "Pricer to identify new cutting stock patterns")
+
+    # item widths
+    widths = [14, 31, 36, 45]
+    # width demand
+    demand = [211, 395, 610, 97]
+    # roll length
+    rollLength = 100
+    assert len(widths) == len(demand)
+
+    # adding the initial variables
+    cutPatternVars = []
+    varNames = []
+    varBaseName = "Pattern"
+    patterns = []
+
+    for i in range(len(widths)):
+        varNames.append(varBaseName + "_" + str(i))
+        cutPatternVars.append(s.addVar(varNames[i], obj = 1.0))
+
+    # adding a linear constraint for the knapsack constraint
+    demandCons = []
+    for i in range(len(widths)):
+        numWidthsPerRoll = float(int(rollLength/widths[i]))
+        demandCons.append(s.addCons(numWidthsPerRoll*cutPatternVars[i] >= demand[i],
+                                    separate = False, modifiable = True))
+        newPattern = [0]*len(widths)
+        newPattern[i] = numWidthsPerRoll
+        patterns.append(newPattern)
+
+    # Setting the pricer_data for use in the init and redcost functions
+    pricer.data = {}
+    pricer.data['var'] = cutPatternVars
+    pricer.data['cons'] = demandCons
+    pricer.data['widths'] = widths
+    pricer.data['demand'] = demand
+    pricer.data['rollLength'] = rollLength
+    pricer.data['patterns'] = patterns
+    pricer.data['redcosts'] = []
+    pricer.data["deactivate"] = True
+
+    # solve problem
+    s.optimize()
+
+    # the optimal solution with normal pricing
+    assert s.isGT(s.getObjVal(), 452.25)