Scheduling constraints

cpmpy/expressions/__init__.py

@@ -22,7 +22,9 @@
 from .variables import boolvar, intvar, cpm_array
 from .variables import BoolVar, IntVar, cparray # Old, to be deprecated
 from .globalconstraints import AllDifferent, AllDifferentExcept0, AllEqual, Circuit, Inverse, Table, Xor, Cumulative, \
-    IfThenElse, GlobalCardinalityCount, DirectConstraint, InDomain, Increasing, Decreasing, IncreasingStrict, DecreasingStrict
+    IfThenElse, GlobalCardinalityCount, DirectConstraint, InDomain, Increasing, Decreasing, IncreasingStrict, \
+    DecreasingStrict, Precedence, NoOverlap
+
 from .globalconstraints import alldifferent, allequal, circuit # Old, to be deprecated
 from .globalfunctions import Maximum, Minimum, Abs, Element, Count, NValue, NValueExcept
 from .core import BoolVal

cpmpy/expressions/globalconstraints.py

@@ -503,6 +503,67 @@ def value(self):
         return True
 
 
+class Precedence(GlobalConstraint):
+    """
+        Constraint enforcing some values have precedence over others.
+        Given an array of variables X and and a list of precedences P:
+        Then in order to satisfy the constraint, if X[i] = P[j+1], then there exists a X[i'] = P[j] with i' < i
+    """
+    def __init__(self, vars, precedence):
+        if not is_any_list(vars):
+            raise TypeError("Precedence expects a list of variables, but got", vars)
+        if not is_any_list(precedence) or any(isinstance(x, Expression) for x in precedence):
+            raise TypeError("Precedence expects a list of values as precedence, but got", precedence)
+        super().__init__("precedence", [vars, precedence])
+
+    def decompose(self):
+        """
+        Decomposition based on:
+        Law, Yat Chiu, and Jimmy HM Lee. "Global constraints for integer and set value precedence."
+        Principles and Practice of Constraint Programming–CP 2004: 10th International Conference, CP 2004
+        """
+        from .python_builtins import any as cpm_any
+
+        args, precedence = self.args
+        constraints = []
+        for s,t in zip(precedence[:-1], precedence[1:]):
+            for j in range(len(args)):
+                constraints += [(args[j] == t).implies(cpm_any(args[:j] == s))]
+        return constraints, []
+
+    def value(self):
+
+        args, precedence = self.args
+        vals = np.array(argvals(args))
+        for s,t in zip(precedence[:-1], precedence[1:]):
+            if vals[0] == t: return False
+            for j in range(len(args)):
+                if vals[j] == t and sum(vals[:j] == s) == 0:
+                    return False
+        return True
+
+
+class NoOverlap(GlobalConstraint):
+
+    def __init__(self, start, dur, end):
+        super().__init__("no_overlap", [start, dur, end])
+
+    def decompose(self):
+        start, dur, end = self.args
+        cons = [s + d == e for s,d,e in zip(start, dur, end)]
+        for (s1, e1), (s2, e2) in all_pairs(zip(start, end)):
+            cons += [(e1 <= s2) | (e2 <= s1)]
+        return cons, []
+    def value(self):
+        start, dur, end = argvals(self.args)
+        if any(s + d != e for s,d,e in zip(start, dur, end)):
+            return False
+        for (s1,d1, e1), (s2,d2, e2) in all_pairs(zip(start,dur, end)):
+            if e1 > s2 and e2 > s1:
+                return False
+        return True
+
+
 class GlobalCardinalityCount(GlobalConstraint):
     """
     GlobalCardinalityCount(vars,vals,occ): The number of occurrences of each value vals[i] in the list of variables vars

cpmpy/expressions/utils.py

@@ -133,7 +133,9 @@ def argval(a):
 
 
 def argvals(arr):
-    return [argval(a) for a in arr]
+    if is_any_list(arr):
+        return [argvals(arg) for arg in arr]
+    return argval(arr)
 
 
 def eval_comparison(str_op, lhs, rhs):

cpmpy/solvers/choco.py

@@ -314,6 +314,7 @@ def transform(self, cpm_expr):
         cpm_cons = toplevel_list(cpm_expr)
         supported = {"min", "max", "abs", "count", "element", "alldifferent", "alldifferent_except0", "allequal",
                      "table", "InDomain", "cumulative", "circuit", "gcc", "inverse", "nvalue", "increasing",
+                     "precedence",
                      "decreasing","strictly_increasing","strictly_decreasing"}
 
         # choco supports reification of any constraint, but has a bug in increasing and decreasing
@@ -536,6 +537,8 @@ def _get_constraint(self, cpm_expr):
                 # Create task variables. Choco can create them only one by one
                 tasks = [self.chc_model.task(s, d, e) for s, d, e in zip(start, dur, end)]
                 return self.chc_model.cumulative(tasks, demand, cap)
+            elif cpm_expr.name == "precedence":
+                return self.chc_model.int_value_precede_chain(self._to_vars(cpm_expr.args[0]), cpm_expr.args[1])
             elif cpm_expr.name == "gcc":
                 vars, vals, occ = cpm_expr.args
                 return self.chc_model.global_cardinality(*self.solver_vars([vars, vals]), self._to_vars(occ))

cpmpy/solvers/minizinc.py

@@ -419,8 +419,9 @@ def transform(self, cpm_expr):
         cpm_cons = toplevel_list(cpm_expr)
         supported = {"min", "max", "abs", "element", "count", "nvalue", "alldifferent", "alldifferent_except0", "allequal",
                      "inverse", "ite" "xor", "table", "cumulative", "circuit", "gcc", "increasing",
+                     "precedence","no_overlap",
                      "decreasing","strictly_increasing","strictly_decreasing"}
-        return decompose_in_tree(cpm_cons, supported, supported_reified=supported - {"circuit"})
+        return decompose_in_tree(cpm_cons, supported, supported_reified=supported - {"circuit", "precedence"})
 
 
     def __add__(self, cpm_expr):
@@ -584,6 +585,15 @@ def zero_based(array):
 
             return format_str.format(args_str[0], args_str[1], args_str[3], args_str[4])
 
+        elif expr.name == "precedence":
+            return "value_precede_chain({},{})".format(args_str[1], args_str[0])
+
+        elif expr.name == "no_overlap":
+            start, dur, end = expr.args
+            durstr = self._convert_expression([s + d == e for s, d, e in zip(start, dur, end)])
+            format_str = "forall(" + durstr + " ++ [disjunctive({},{})])"
+            return format_str.format(args_str[0], args_str[1])
+
         elif expr.name == 'ite':
             cond, tr, fal = expr.args
             return "if {} then {} else {} endif".format(self._convert_expression(cond), self._convert_expression(tr),

cpmpy/solvers/ortools.py

@@ -330,7 +330,7 @@ def transform(self, cpm_expr):
         :return: list of Expression
         """
         cpm_cons = toplevel_list(cpm_expr)
-        supported = {"min", "max", "abs", "element", "alldifferent", "xor", "table", "cumulative", "circuit", "inverse"}
+        supported = {"min", "max", "abs", "element", "alldifferent", "xor", "table", "cumulative", "circuit", "inverse", "no_overlap"}
         cpm_cons = decompose_in_tree(cpm_cons, supported)
         cpm_cons = flatten_constraint(cpm_cons)  # flat normal form
         cpm_cons = reify_rewrite(cpm_cons, supported=frozenset(['sum', 'wsum']))  # constraints that support reification
@@ -470,6 +470,10 @@ def _post_constraint(self, cpm_expr, reifiable=False):
                 start, dur, end, demand, cap = self.solver_vars(cpm_expr.args)
                 intervals = [self.ort_model.NewIntervalVar(s,d,e,f"interval_{s}-{d}-{e}") for s,d,e in zip(start,dur,end)]
                 return self.ort_model.AddCumulative(intervals, demand, cap)
+            elif cpm_expr.name == "no_overlap":
+                start, dur, end = self.solver_vars(cpm_expr.args)
+                intervals = [self.ort_model.NewIntervalVar(s,d,e, f"interval_{s}-{d}-{d}") for s,d,e in zip(start,dur,end)]
+                return self.ort_model.add_no_overlap(intervals)
             elif cpm_expr.name == "circuit":
                 # ortools has a constraint over the arcs, so we need to create these
                 # when using an objective over arcs, using these vars direclty is recommended

tests/test_constraints.py

@@ -16,8 +16,9 @@
 # Exclude some global constraints for solvers
 
 NUM_GLOBAL = {
-    "AllEqual", "AllDifferent", "AllDifferentExcept0", "Cumulative", "GlobalCardinalityCount", "InDomain", "Inverse", "Table", "Circuit",
+    "AllEqual", "AllDifferent", "AllDifferentExcept0" , "GlobalCardinalityCount", "InDomain", "Inverse", "Table", "Circuit",
     "Increasing", "IncreasingStrict", "Decreasing", "DecreasingStrict",
+    "Precedence", "Cumulative", "NoOverlap",
     # also global functions
     "Abs", "Element", "Minimum", "Maximum", "Count", "NValue", "NValueExcept"
 }
@@ -194,6 +195,14 @@ def global_constraints(solver):
             demand = [4, 5, 7]
             cap = 10
             expr = Cumulative(s, dur, e, demand, cap)
+        elif name == "Precedence":
+            x = intvar(0,5, shape=3, name="x")
+            expr = cls(x, [3,1,0])
+        elif name == "NoOverlap":
+            s = intvar(0, 10, shape=3, name="start")
+            e = intvar(0, 10, shape=3, name="end")
+            dur = [1,4,3]
+            expr = cls(s, dur, e)
         elif name == "GlobalCardinalityCount":
             vals = [1, 2, 3]
             cnts = intvar(0,10,shape=3)

tests/test_globalconstraints.py

@@ -708,6 +708,32 @@ def check_true():
 
         cp.Model(cons).solveAll(solver='minizinc')
 
+
+    def test_precedence(self):
+        iv = cp.intvar(0,5, shape=6, name="x")
+
+        cons = cp.Precedence(iv, [0,2,1])
+        self.assertTrue(cp.Model([cons, iv == [5,0,2,0,0,1]]).solve())
+        self.assertTrue(cons.value())
+        self.assertTrue(cp.Model([cons, iv == [0,0,0,0,0,0]]).solve())
+        self.assertTrue(cons.value())
+        self.assertFalse(cp.Model([cons, iv == [0,1,2,0,0,0]]).solve())
+
+
+    def test_no_overlap(self):
+        start = cp.intvar(0,5, shape=3)
+        end = cp.intvar(0,5, shape=3)
+        cons = cp.NoOverlap(start, [2,1,1], end)
+        self.assertTrue(cp.Model(cons).solve())
+        self.assertTrue(cons.value())
+        self.assertTrue(cp.Model(cons.decompose()).solve())
+        self.assertTrue(cons.value())
+
+        def check_val():
+            assert cons.value() is False
+
+        cp.Model(~cons).solveAll(display=check_val)
+
 class TestBounds(unittest.TestCase):
     def test_bounds_minimum(self):
         x = cp.intvar(-8, 8)