我有一个实施方式,应该为货件设置多个时间窗口:
def _set_allowed_time_window(time_dimension, index, time_windows: list):
""" Sets the appropriate time windows for a node. """
# ortools lacks a function to set a list of time windows
# workaround is to set the min and max of a list of sorted time windows as the allowed range
# and then to restrict the times in between the allowed time windows
# see https://github.com/google/or-tools/issues/456 and
# https://groups.google.com/forum/#!topic/or-tools-discuss/MBq1TcqSQTI
earliest_start = int(time_windows[0][0])
latest_end = int(time_windows[len(time_windows)-1][1])
time_dimension.CumulVar(index).SetRange(earliest_start, latest_end)
for tw_index, time_window in enumerate(time_windows):
if tw_index == len(time_windows)-1:
break
time_window_end = int(time_window[1])
next_time_window_start = int(time_windows[tw_index+1][0])
time_dimension.CumulVar(index).RemoveInterval(time_window_end, next_time_window_start)
逻辑上似乎没有什么错,但是除非我删除行time_dimension.CumulVar(index).RemoveInterval(time_window_end, next_time_window_start)
,否则or-tools无法返回解决方案。有什么想法我在这里做错了吗?
这里time_windows
是一个lis,例如:[[100,200],[300,400]],而index
是从NodeToIndex
检索的索引。
答案 0 :(得分:2)
问题似乎确实存在于注释中提到的FirstSolutionStrategy中。当一切都出现时,未分配的or-tools根本无法构建第一个解决方案。不幸的是,从日志中并不清楚。我在FirstSolutionStrategy
的{{1}}和ALL_UNEPRFORMED
上取得了成功。
不幸的是,在我的情况下,PATH_MOST_CONSTRAINED_ARC
无法解决琐碎的案件,但是ALL_UNPERFORMED
运作良好。我只希望算法有更深入的描述,以便更轻松地选择合适的算法。