Removed assignment_b.py

python/assignment_b.py

@@ -1,119 +0,0 @@
-# Copyright 2010 Hakan Kjellerstrand hakank@bonetmail.com
-#
-# Licensed under the Apache License, Version 2.0 (the "License"); 
-# you may not use this file except in compliance with the License. 
-# You may obtain a copy of the License at 
-#
-#     http://www.apache.org/licenses/LICENSE-2.0 
-#
-# Unless required by applicable law or agreed to in writing, software 
-# distributed under the License is distributed on an "AS IS" BASIS, 
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 
-# See the License for the specific language governing permissions and 
-# limitations under the License. 
-
-"""
-
-  Assignment problem in Google CP Solver.
-
-  Winston 'Operations Research', Assignment Problems, page 393f
-  (generalized version with added test column)
-
-  Compare with the following models:
-  * Comet   : http://www.hakank.org/comet/assignment.co
-  * ECLiPSE : http://www.hakank.org/eclipse/assignment.ecl
-  * Gecode  : http://www.hakank.org/gecode/assignment.cpp
-  * MiniZinc: http://www.hakank.org/minizinc/assignment.mzn
-  * Tailor/Essence': http://www.hakank.org/tailor/assignment.eprime
-  * SICStus: http://hakank.org/sicstus/assignment.pl
-
-  This model was created by Hakan Kjellerstrand (hakank@bonetmail.com)
-  Also see my other Google CP Solver models: http://www.hakank.org/google_or_tools/
-"""
-
-from constraint_solver import pywrapcp
-
-
-def main(cost, rows, cols):
-    # Create the solver.
-    solver = pywrapcp.Solver('n-queens')
-
-    #
-    # data
-    #
-    
-
-    # declare variables
-    total_cost = solver.IntVar(0, 100, 'total_cost')
-    x = {}
-    for i in range(rows):
-        for j in range(cols):
-            x[(i, j)] = solver.IntVar(0, 1, 'x(%i,%i)' % (i, j))
-    x_flat = [x[(i[j] for i in range(rows) for j in range(cols)]    
-
-    #
-    # constraints
-    #
-    solver.Add(total_cost == solver.Sum([solver.ScalProd(x_row,  cost_row) for (x_row, cost_row) in zip(x, cost)]))
-    
-        
-    # exacly one assignment per row, all rows must be assigned
-    for row in range(rows):
-        r = [x[row][j] for j in range(cols)]
-        solver.Add(solver.Sum(r) == 1)
-
-    # zero or one assignments per column
-    for col in range(cols):
-        c = [x[i][col] for i in range(rows)]        
-        solver.Add(solver.Sum(c) <= 1)
-    
-
-    objective = solver.Minimize(total_cost, 1)
-
-    #
-    # solution and search
-    #
-    solution = solver.Assignment()
-    solution.Add(x_flat)
-    solution.Add(total_cost)    
-
-
-    # db: DecisionBuilder
-    db = solver.Phase(x_flat,
-                 solver.INT_VAR_SIMPLE,
-                 solver.ASSIGN_MIN_VALUE)
-    
-    solver.NewSearch(db,[objective])
-    num_solutions = 0
-    while solver.NextSolution():  
-        print "total_cost:", total_cost.Value()
-        xval = [x[i][j].Value() for i in range(rows) for j in range(cols)]
-        print "x:", xval
-        for i in range(rows):
-            for j in range(cols):
-                print xval[i*cols+j],
-            print
-        print
-        num_solutions += 1        
-    solver.EndSearch()
-    
-    print
-    print "num_solutions:", num_solutions
-    print "failures:", solver.failures()
-    print "branches:", solver.branches()
-    print "wall_time:", solver.wall_time()
-
-
-# Problem instance
-# hakank: I added the fifth column to make it more
-#         interesting
-rows = 4
-cols = 5
-cost = [[14,  5, 8,  7,   15],
-        [ 2, 12, 6,  5,    3],
-        [ 7,  8, 3,  9,    7],
-        [ 2,  4, 6, 10,    1]
-       ]
-
-if __name__ == '__main__':
-    main(cost, rows, cols)