1# Copyright 2010-2021 Google LLC 2# Licensed under the Apache License, Version 2.0 (the "License"); 3# you may not use this file except in compliance with the License. 4# You may obtain a copy of the License at 5# 6# http://www.apache.org/licenses/LICENSE-2.0 7# 8# Unless required by applicable law or agreed to in writing, software 9# distributed under the License is distributed on an "AS IS" BASIS, 10# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 11# See the License for the specific language governing permissions and 12# limitations under the License. 13"""Reallocate production to smooth it over years.""" 14 15 16import collections 17 18from ortools.sat.python import cp_model 19 20 21def main(): 22 23 # Data 24 data_0 = [ 25 [107, 107, 107, 0, 0], # pr1 26 [0, 47, 47, 47, 0], # pr2 27 [10, 10, 10, 0, 0], # pr3 28 [0, 55, 55, 55, 55], # pr4 29 ] 30 31 data_1 = [ 32 [119444030, 0, 0, 0], 33 [34585586, 38358559, 31860661, 0], 34 [19654655, 21798799, 18106106, 0], 35 [298836792, 0, 0, 0], 36 [3713428, 4118530, 4107277, 3072018], 37 [6477273, 7183884, 5358471, 0], 38 [1485371, 1647412, 1642911, 1228807] 39 ] 40 41 data_2 = [ 42 [1194440, 0, 0, 0], 43 [345855, 383585, 318606, 0], 44 [196546, 217987, 181061, 0], 45 [2988367, 0, 0, 0], 46 [37134, 41185, 41072, 30720], 47 [64772, 71838, 53584, 0], 48 [14853, 16474, 16429, 12288] 49 ] 50 51 pr = data_0 52 53 num_pr = len(pr) 54 num_years = len(pr[1]) 55 total = sum(pr[p][y] for p in range(num_pr) for y in range(num_years)) 56 avg = total // num_years 57 58 # Model 59 model = cp_model.CpModel() 60 61 # Variables 62 delta = model.NewIntVar(0, total, 'delta') 63 64 contributions_per_years = collections.defaultdict(list) 65 contributions_per_prs = collections.defaultdict(list) 66 all_contribs = {} 67 68 for p, inner_l in enumerate(pr): 69 for y, item in enumerate(inner_l): 70 if item != 0: 71 contrib = model.NewIntVar(0, total, 'r%d c%d' % (p, y)) 72 contributions_per_years[y].append(contrib) 73 contributions_per_prs[p].append(contrib) 74 all_contribs[p, y] = contrib 75 76 year_var = [ 77 model.NewIntVar(0, total, 'y[%i]' % i) for i in range(num_years) 78 ] 79 80 # Constraints 81 82 # Maintain year_var. 83 for y in range(num_years): 84 model.Add(year_var[y] == sum(contributions_per_years[y])) 85 86 # Fixed contributions per pr. 87 for p in range(num_pr): 88 model.Add(sum(pr[p]) == sum(contributions_per_prs[p])) 89 90 # Link delta with variables. 91 for y in range(num_years): 92 model.Add(year_var[y] >= avg - delta) 93 94 for y in range(num_years): 95 model.Add(year_var[y] <= avg + delta) 96 97 # Solve and output 98 model.Minimize(delta) 99 100 # Solve model. 101 solver = cp_model.CpSolver() 102 status = solver.Solve(model) 103 104 # Output solution. 105 if status == cp_model.OPTIMAL: 106 print('Data') 107 print(' - total = ', total) 108 print(' - year_average = ', avg) 109 print(' - number of projects = ', num_pr) 110 print(' - number of years = ', num_years) 111 112 print(' - input production') 113 for p in range(num_pr): 114 for y in range(num_years): 115 if pr[p][y] == 0: 116 print(' ', end='') 117 else: 118 print('%10i' % pr[p][y], end='') 119 print() 120 121 print('Solution') 122 for p in range(num_pr): 123 for y in range(num_years): 124 if pr[p][y] == 0: 125 print(' ', end='') 126 else: 127 print('%10i' % solver.Value(all_contribs[p, y]), end='') 128 print() 129 130 for y in range(num_years): 131 print('%10i' % solver.Value(year_var[y]), end='') 132 print() 133 134 135if __name__ == '__main__': 136 main() 137