reformat python files as tab length = 4 now
This commit is contained in:
Laurent Perron
@@ -26,154 +26,157 @@ from ortools.sat.python import cp_model
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# Create a solution printer.
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class SolutionPrinter(cp_model.CpSolverSolutionCallback):
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"""Print intermediate solutions."""
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"""Print intermediate solutions."""
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def __init__(self, values, colors, all_groups, all_items, item_in_group):
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cp_model.CpSolverSolutionCallback.__init__(self)
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self.__solution_count = 0
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self.__values = values
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self.__colors = colors
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self.__all_groups = all_groups
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self.__all_items = all_items
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self.__item_in_group = item_in_group
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def __init__(self, values, colors, all_groups, all_items, item_in_group):
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cp_model.CpSolverSolutionCallback.__init__(self)
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self.__solution_count = 0
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self.__values = values
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self.__colors = colors
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self.__all_groups = all_groups
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self.__all_items = all_items
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self.__item_in_group = item_in_group
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def OnSolutionCallback(self):
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print('Solution %i' % self.__solution_count)
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self.__solution_count += 1
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def OnSolutionCallback(self):
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print('Solution %i' % self.__solution_count)
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self.__solution_count += 1
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print(' objective value = %i' % self.ObjectiveValue())
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groups = {}
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sums = {}
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for g in self.__all_groups:
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groups[g] = []
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sums[g] = 0
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for item in self.__all_items:
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if self.BooleanValue(self.__item_in_group[(item, g)]):
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groups[g].append(item)
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sums[g] += self.__values[item]
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print(' objective value = %i' % self.ObjectiveValue())
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groups = {}
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sums = {}
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for g in self.__all_groups:
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groups[g] = []
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sums[g] = 0
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for item in self.__all_items:
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if self.BooleanValue(self.__item_in_group[(item, g)]):
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groups[g].append(item)
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sums[g] += self.__values[item]
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for g in self.__all_groups:
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group = groups[g]
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print('group %i: sum = %0.2f [' % (g, sums[g]), end='')
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for item in group:
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value = self.__values[item]
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color = self.__colors[item]
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print(' (%i, %i, %i)' % (item, value, color), end='')
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print(']')
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for g in self.__all_groups:
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group = groups[g]
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print('group %i: sum = %0.2f [' % (g, sums[g]), end='')
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for item in group:
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value = self.__values[item]
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color = self.__colors[item]
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print(' (%i, %i, %i)' % (item, value, color), end='')
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print(']')
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def SolutionCount(self):
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return self.__solution_count
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def SolutionCount(self):
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return self.__solution_count
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def main():
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# Data.
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num_groups = 10
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num_items = 100
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num_colors = 3
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min_items_of_same_color_per_group = 4
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# Data.
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num_groups = 10
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num_items = 100
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num_colors = 3
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min_items_of_same_color_per_group = 4
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all_groups = range(num_groups)
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all_items = range(num_items)
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all_colors = range(num_colors)
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all_groups = range(num_groups)
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all_items = range(num_items)
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all_colors = range(num_colors)
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# Values for each items.
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values = [1 + i + (i * i // 200) for i in all_items]
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# Color for each item (simple modulo).
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colors = [i % num_colors for i in all_items]
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# Values for each items.
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values = [1 + i + (i * i // 200) for i in all_items]
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# Color for each item (simple modulo).
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colors = [i % num_colors for i in all_items]
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sum_of_values = sum(values)
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average_sum_per_group = sum_of_values // num_groups
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sum_of_values = sum(values)
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average_sum_per_group = sum_of_values // num_groups
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num_items_per_group = num_items // num_groups
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num_items_per_group = num_items // num_groups
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# Collect all items in a given color.
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items_per_color = {}
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for c in all_colors:
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items_per_color[c] = []
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for i in all_items:
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if colors[i] == c:
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items_per_color[c].append(i)
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print('Model has %i items, %i groups, and %i colors' % (num_items, num_groups,
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num_colors))
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print(' average sum per group = %i' % average_sum_per_group)
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# Model.
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model = cp_model.CpModel()
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item_in_group = {}
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for i in all_items:
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for g in all_groups:
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item_in_group[(i, g)] = model.NewBoolVar('item %d in group %d' % (i, g))
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# Each group must have the same size.
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for g in all_groups:
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model.Add(
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sum(item_in_group[(i, g)] for i in all_items) == num_items_per_group)
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# One item must belong to exactly one group.
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for i in all_items:
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model.Add(sum(item_in_group[(i, g)] for g in all_groups) == 1)
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# The deviation of the sum of each items in a group against the average.
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e = model.NewIntVar(0, 550, 'epsilon')
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# Constrain the sum of values in one group around the average sum per group.
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for g in all_groups:
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model.Add(
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sum(item_in_group[(i, g)] * values[i]
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for i in all_items) <= average_sum_per_group + e)
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model.Add(
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sum(item_in_group[(i, g)] * values[i]
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for i in all_items) >= average_sum_per_group - e)
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# color_in_group variables.
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color_in_group = {}
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for g in all_groups:
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# Collect all items in a given color.
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items_per_color = {}
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for c in all_colors:
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color_in_group[(c,
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g)] = model.NewBoolVar('color %d is in group %d' % (c, g))
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items_per_color[c] = []
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for i in all_items:
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if colors[i] == c:
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items_per_color[c].append(i)
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# Item is in a group implies its color is in that group.
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for i in all_items:
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print('Model has %i items, %i groups, and %i colors' %
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(num_items, num_groups, num_colors))
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print(' average sum per group = %i' % average_sum_per_group)
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# Model.
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model = cp_model.CpModel()
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item_in_group = {}
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for i in all_items:
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for g in all_groups:
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item_in_group[(i, g)] = model.NewBoolVar(
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'item %d in group %d' % (i, g))
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# Each group must have the same size.
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for g in all_groups:
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model.AddImplication(item_in_group[(i, g)], color_in_group[(colors[i],
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g)])
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model.Add(
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sum(item_in_group[(i, g)]
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for i in all_items) == num_items_per_group)
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# If a color is in a group, it must contains at least
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# min_items_of_same_color_per_group items from that color.
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for c in all_colors:
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# One item must belong to exactly one group.
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for i in all_items:
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model.Add(sum(item_in_group[(i, g)] for g in all_groups) == 1)
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# The deviation of the sum of each items in a group against the average.
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e = model.NewIntVar(0, 550, 'epsilon')
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# Constrain the sum of values in one group around the average sum per group.
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for g in all_groups:
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literal = color_in_group[(c, g)]
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model.Add(
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sum(item_in_group[(i, g)] for i in items_per_color[c]) >=
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min_items_of_same_color_per_group).OnlyEnforceIf(literal)
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model.Add(
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sum(item_in_group[(i, g)] * values[i]
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for i in all_items) <= average_sum_per_group + e)
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model.Add(
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sum(item_in_group[(i, g)] * values[i]
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for i in all_items) >= average_sum_per_group - e)
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# Compute the maximum number of colors in a group.
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max_color = num_items_per_group // min_items_of_same_color_per_group
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# Redundant contraint: The problem does not solve in reasonable time without it.
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if max_color < num_colors:
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# color_in_group variables.
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color_in_group = {}
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for g in all_groups:
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model.Add(sum(color_in_group[(c, g)] for c in all_colors) <= max_color)
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for c in all_colors:
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color_in_group[(c, g)] = model.NewBoolVar(
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'color %d is in group %d' % (c, g))
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# Minimize epsilon
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model.Minimize(e)
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# Item is in a group implies its color is in that group.
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for i in all_items:
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for g in all_groups:
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model.AddImplication(item_in_group[(i, g)],
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color_in_group[(colors[i], g)])
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solver = cp_model.CpSolver()
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solution_printer = SolutionPrinter(values, colors, all_groups, all_items,
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item_in_group)
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status = solver.SolveWithSolutionCallback(model, solution_printer)
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# If a color is in a group, it must contains at least
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# min_items_of_same_color_per_group items from that color.
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for c in all_colors:
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for g in all_groups:
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literal = color_in_group[(c, g)]
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model.Add(
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sum(item_in_group[(i, g)] for i in items_per_color[c]) >=
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min_items_of_same_color_per_group).OnlyEnforceIf(literal)
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if status == cp_model.OPTIMAL:
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print('Optimal epsilon: %i' % solver.ObjectiveValue())
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print('Statistics')
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print(' - conflicts : %i' % solver.NumConflicts())
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print(' - branches : %i' % solver.NumBranches())
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print(' - wall time : %f s' % solver.WallTime())
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else:
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print('No solution found')
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# Compute the maximum number of colors in a group.
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max_color = num_items_per_group // min_items_of_same_color_per_group
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# Redundant contraint: The problem does not solve in reasonable time without it.
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if max_color < num_colors:
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for g in all_groups:
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model.Add(
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sum(color_in_group[(c, g)] for c in all_colors) <= max_color)
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# Minimize epsilon
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model.Minimize(e)
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solver = cp_model.CpSolver()
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solution_printer = SolutionPrinter(values, colors, all_groups, all_items,
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item_in_group)
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status = solver.SolveWithSolutionCallback(model, solution_printer)
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if status == cp_model.OPTIMAL:
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print('Optimal epsilon: %i' % solver.ObjectiveValue())
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print('Statistics')
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print(' - conflicts : %i' % solver.NumConflicts())
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print(' - branches : %i' % solver.NumBranches())
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print(' - wall time : %f s' % solver.WallTime())
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else:
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print('No solution found')
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if __name__ == '__main__':
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main()
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main()
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