# 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. """ Young tableaux in Google CP Solver. See http://mathworld.wolfram.com/YoungTableau.html and http://en.wikipedia.org/wiki/Young_tableau ''' The partitions of 4 are {4}, {3,1}, {2,2}, {2,1,1}, {1,1,1,1} And the corresponding standard Young tableaux are: 1. 1 2 3 4 2. 1 2 3 1 2 4 1 3 4 4 3 2 3. 1 2 1 3 3 4 2 4 4 1 2 1 3 1 4 3 2 2 4 4 3 5. 1 2 3 4 ''' Thanks to Laurent Perron for improving this model. Compare with the following models: * MiniZinc: http://www.hakank.org/minizinc/young_tableaux.mzn * Choco : http://www.hakank.org/choco/YoungTableuax.java * JaCoP : http://www.hakank.org/JaCoP/YoungTableuax.java * Comet : http://www.hakank.org/comet/young_tableaux.co * Gecode : http://www.hakank.org/gecode/young_tableaux.cpp * ECLiPSe : http://www.hakank.org/eclipse/young_tableaux.ecl * Tailor/Essence' : http://www.hakank.org/tailor/young_tableaux.eprime * SICStus: http://hakank.org/sicstus/young_tableaux.pl * Zinc: http://hakank.org/minizinc/young_tableaux.zinc 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 __future__ import print_function import sys from ortools.constraint_solver import pywrapcp def main(n=5): # Create the solver. solver = pywrapcp.Solver("Problem") # # data # print("n:", n) # # declare variables # x = {} for i in range(n): for j in range(n): x[(i, j)] = solver.IntVar(1, n + 1, "x(%i,%i)" % (i, j)) x_flat = [x[(i, j)] for i in range(n) for j in range(n)] # partition structure p = [solver.IntVar(0, n + 1, "p%i" % i) for i in range(n)] # # constraints # # 1..n is used exactly once for i in range(1, n + 1): solver.Add(solver.Count(x_flat, i, 1)) solver.Add(x[(0, 0)] == 1) # row wise for i in range(n): for j in range(1, n): solver.Add(x[(i, j)] >= x[(i, j - 1)]) # column wise for j in range(n): for i in range(1, n): solver.Add(x[(i, j)] >= x[(i - 1, j)]) # calculate the structure (the partition) for i in range(n): # MiniZinc/Zinc version: # p[i] == sum(j in 1..n) (bool2int(x[i,j] <= n)) b = [solver.IsLessOrEqualCstVar(x[(i, j)], n) for j in range(n)] solver.Add(p[i] == solver.Sum(b)) solver.Add(solver.Sum(p) == n) for i in range(1, n): solver.Add(p[i - 1] >= p[i]) # # solution and search # solution = solver.Assignment() solution.Add(x_flat) solution.Add(p) # db: DecisionBuilder db = solver.Phase(x_flat + p, solver.CHOOSE_FIRST_UNBOUND, solver.ASSIGN_MIN_VALUE) solver.NewSearch(db) num_solutions = 0 while solver.NextSolution(): print("p:", [p[i].Value() for i in range(n)]) print("x:") for i in range(n): for j in range(n): val = x_flat[i * n + j].Value() if val <= n: print(val, end=' ') if p[i].Value() > 0: print() print() num_solutions += 1 solver.EndSearch() print() print("num_solutions:", num_solutions) print("failures:", solver.Failures()) print("branches:", solver.Branches()) print("WallTime:", solver.WallTime()) n = 5 if __name__ == "__main__": if len(sys.argv) > 1: n = int(sys.argv[1]) main(n)