Moving Pyro examples to example folder

examples/pyro/sudoku.py

@@ -0,0 +1,101 @@
+from pyomo.environ import *
+
+# create a standard python dict for mapping subsquares to
+# the list (row,col) entries
+subsq_to_row_col = dict()
+
+subsq_to_row_col[1] = [(i,j) for i in range(1,4) for j in range(1,4)]
+subsq_to_row_col[2] = [(i,j) for i in range(1,4) for j in range(4,7)]
+subsq_to_row_col[3] = [(i,j) for i in range(1,4) for j in range(7,10)]
+
+subsq_to_row_col[4] = [(i,j) for i in range(4,7) for j in range(1,4)]
+subsq_to_row_col[5] = [(i,j) for i in range(4,7) for j in range(4,7)]
+subsq_to_row_col[6] = [(i,j) for i in range(4,7) for j in range(7,10)]
+
+subsq_to_row_col[7] = [(i,j) for i in range(7,10) for j in range(1,4)]
+subsq_to_row_col[8] = [(i,j) for i in range(7,10) for j in range(4,7)]
+subsq_to_row_col[9] = [(i,j) for i in range(7,10) for j in range(7,10)]
+
+# creates the sudoku model for a 10x10 board, where the
+# input board is a list of fixed numbers specified in
+# (row, col, val) tuples.
+def create_sudoku_model(board):
+
+    model = ConcreteModel()
+
+    # store the starting board for the model
+    model.board = board
+
+    # create sets for rows columns and squares
+    model.ROWS = RangeSet(1,9)
+    model.COLS = RangeSet(1,9)
+    model.SUBSQUARES = RangeSet(1,9)
+    model.VALUES = RangeSet(1,9)
+
+    # create the binary variables to define the values
+    model.y = Var(model.ROWS, model.COLS, model.VALUES, within=Binary)
+
+    # fix variables based on the current board
+    for (r,c,v) in board:
+        model.y[r,c,v].fix(1)
+
+    # create the objective - this is a feasibility problem
+    # so we just make it a constant
+    model.obj = Objective(expr= 1.0)
+
+# @row_col_cons:
+    # exactly one number in each row
+    def _RowCon(model, r, v):
+        return sum(model.y[r,c,v] for c in model.COLS) == 1
+    model.RowCon = Constraint(model.ROWS, model.VALUES, rule=_RowCon)
+
+    # exactly one nubmer in each column
+    def _ColCon(model, c, v):
+        return sum(model.y[r,c,v] for r in model.ROWS) == 1
+    model.ColCon = Constraint(model.COLS, model.VALUES, rule=_ColCon)
+# @:row_col_cons
+
+# @subsq_con:
+    # exactly one number in each subsquare
+    def _SqCon(model, s, v):
+        return sum(model.y[r,c,v] for (r,c) in subsq_to_row_col[s]) == 1
+    model.SqCon = Constraint(model.SUBSQUARES, model.VALUES, rule=_SqCon)
+# @:subsq_con
+
+# @num_con:
+    # exactly one number in each cell
+    def _ValueCon(model, r, c):
+        return sum(model.y[r,c,v] for v in model.VALUES) == 1
+    model.ValueCon = Constraint(model.ROWS, model.COLS, rule=_ValueCon)
+# @:num_con
+
+    return model
+
+# use this function to add a new integer cut to the model.
+def add_integer_cut(model):
+    # add the ConstraintList to store the IntegerCuts if
+    # it does not already exist
+    if not hasattr(model, "IntegerCuts"):
+        model.IntegerCuts = ConstraintList()
+
+    # add the integer cut corresponding to the current
+    # solution in the model
+    cut_expr = 0.0
+    for r in model.ROWS:
+        for c in model.COLS:
+            for v in model.VALUES:
+                if not model.y[r,c,v].fixed:
+                    # check if the binary variable is on or off
+                    # note, it may not be exactly 1
+                    if value(model.y[r,c,v]) >= 0.5:
+                        cut_expr += (1.0 - model.y[r,c,v])
+                    else:
+                        cut_expr += model.y[r,c,v]
+    model.IntegerCuts.add(cut_expr >= 1)
+
+# prints the current solution stored in the model
+def print_solution(model):
+    for r in model.ROWS:
+        print('   '.join(str(v) for c in model.COLS
+                         for v in model.VALUES
+                         if value(model.y[r,c,v]) >= 0.5))

examples/pyro/sudoku_run.py

@@ -0,0 +1,35 @@
+from pyomo.opt import (SolverFactory,
+                       TerminationCondition)
+from sudoku import (create_sudoku_model,
+                    print_solution,
+                    add_integer_cut)
+
+# define the board
+board = [(1,1,5),(1,2,3),(1,5,7), \
+         (2,1,6),(2,4,1),(2,5,9),(2,6,5), \
+         (3,2,9),(3,3,8),(3,8,6), \
+         (4,1,8),(4,5,6),(4,9,3), \
+         (5,1,4),(5,4,8),(5,6,3),(5,9,1), \
+         (6,1,7),(6,5,2),(6,9,6), \
+         (7,2,6),(7,7,2),(7,8,8), \
+         (8,4,4),(8,5,1),(8,6,9),(8,9,5), \
+         (9,5,8),(9,8,7),(9,9,9)]
+
+model = create_sudoku_model(board)
+
+solution_count = 0
+while 1:
+
+    with SolverFactory("glpk") as opt:
+        results = opt.solve(model)
+        if results.solver.termination_condition != \
+           TerminationCondition.optimal:
+            print("All board solutions have been found")
+            break
+
+    solution_count += 1
+
+    add_integer_cut(model)
+
+    print("Solution #%d" % (solution_count))
+    print_solution(model)

examples/pyro/sudoku_run.txt

@@ -0,0 +1,15 @@
+WARNING: Constant objective detected, replacing with a placeholder to prevent
+    solver failure.
+Solution #1
+5   3   4   6   7   8   9   1   2
+6   7   2   1   9   5   3   4   8
+1   9   8   3   4   2   5   6   7
+8   5   9   7   6   1   4   2   3
+4   2   6   8   5   3   7   9   1
+7   1   3   9   2   4   8   5   6
+9   6   1   5   3   7   2   8   4
+2   8   7   4   1   9   6   3   5
+3   4   5   2   8   6   1   7   9
+WARNING: Constant objective detected, replacing with a placeholder to prevent
+    solver failure.
+All board solutions have been found