beta = [set() for col in range(n)]
for row, col in transpose(A.nonzero()):
alpha[row].add(col)
beta[col].add(row)
self.A = A
self.costs = array(costs)
self.nr_tasks, self.nr_rotations = m, n
self.alpha = map(frozenset, alpha)
self.beta = map(frozenset, beta)
def __repr__(self):
return "<CSP problem, %dx%d>" % (self.nr_tasks, self.nr_rotations)
Solution = namedtuple("Solution", "columns covering fitness unfitness")
def make_solution(problem, columns):
covering = dot(problem.A, columns)
fitness = dot(problem.costs, columns)
unfitness = sum(abs(covering - 1))
return Solution(columns, covering, fitness, unfitness)
def initial_solution(problem):
columns = zeros(problem.nr_rotations, dtype="uint8")
I = frozenset(range(problem.nr_tasks))
S, U = set(), set(I)
while U:
i = choice(list(U))
#!/usr/bin/env python
from csp import CrewSchedulingProblem, namedtuple
from random import choice, random
from functools import partial
from operator import attrgetter
from sys import stdout
range = xrange
Candidate = namedtuple('Candidate', 'rotation, greedy_cost')
def DEBUG_RCL(candidates, rcl, selected_candidate, stream=stdout):
min_cost = candidates[0].greedy_cost
max_cost = candidates[-1].greedy_cost
def c_repr(c):
r = c.rotation
s = '%s:%d:%d' % (str(r.tasks), r.cost, c.greedy_cost)
bold = 1 if c == selected_candidate else 0
color = 31 if c.greedy_cost == max_cost else None
if c in rcl:
color = 32 if c.greedy_cost == min_cost else 36
if color:
return '\033[%d;49;%dm%s\033[0m' % (bold, color, s)
return s
data = (len(candidates), len(rcl), min_cost, max_cost)
stream.write('#candidate rotations: %d, #rcl: %d, cost range: [%d, %d]\n' % data)
stream.write(' '.join(c_repr(c) for c in candidates))
stream.write('\n')
def DEBUG_SOLUTION(rotations, stream=stdout):
cost = sum(r.cost for r in rotations)