是“互换搬厂”吗？值得付出努力吗？
我注意到，对于 Cloudbalancing 等问题，存在移动工厂来生成移动和交换。 “移动移动”将云进程从一台计算机转移到另一台计算机。 “交换移动”交换来自各自计算机的任意两个进程。
我正在开发一个时间表应用程序。
subjectTeacherHour（科目和教师的组合）有 仅是可以为其分配的期间的子集。如果 Jane 在一节课上教 6 个小时，则必须为每个 6 个subjectTeacherHour分配一个Period（可能为 30 个Period）该类的；与 cloudbalance 示例不同，在 cloudbalance 中，进程可以移动到任何计算机。- 只能为一个
subjectTeacherHour分配一个Period（自然地）。
它尝试将 subjectTeacherHour 放置到符合条件的 Periods 中，直到找到最佳组合。
优点
...但是，正如巡回锦标赛的示例所证明的那样，如果您可以删除 通过使用某组大招的硬约束，你就可以获胜 性能和可扩展性...
...`[有大动作的版本]评估不可行的程度要低很多 解决方案，使其能够超越简单的解决方案 版本....
...使用多个选择器通常是一个好主意，混合良好 颗粒移动和课程颗粒移动：...
虽然只有一个 subjectTeacher 可以分配给 Period，但求解器必须暂时打破这样的约束，以发现交换两个特定的 >周期分配会带来更好的解决方案。互换举措“拆除了这两个州之间的这堵砖墙”。
因此，交换举措有助于更快地找到更好的解决方案。
缺点
subjectTeacher仅具有可分配的Period的子集。因此，找到任意两个 subjectTeacher 之间的相交（共同）时间有点困难（但可以通过一种优雅的方式实现：从对象属性中查找重叠值的好算法/技术？ ）。
它只会给我带来时间和最优性方面的微小收益吗？
我还担心两种移动可能会导致疯狂交互，从而导致陷入糟糕的解决方案。
I noticed that for problems such as Cloudbalancing, move factories exist to generate moves and swaps. A "move move" transfers a cloud process from one computer to another. A "swap move" swaps any two processes from their respective computers.
I am developing a timetabling application.
- A
subjectTeacherHour(a combination of subject and teacher) have
only a subset ofPeriods to which they may be assigned. If Jane teaches 6 hours at a class, there are 6subjectTeacherHours each which have to be allocated aPeriod, from a possible 30Periods of that class ;unlike the cloudbalance example, where a process can move to any computer. - Only one
subjectTeacherHourmay be allocated aPeriod(naturally).
It tries to place subjectTeacherHour to eligible Periods , till an optimal combination is found.
Pros
The manual seems to recommend it.
...However, as the traveling tournament example proves, if you can remove
a hard constraint by using a certain set of big moves, you can win
performance and scalability......The `[version with big moves] evaluates a lot less unfeasible
solutions, which enables it to outperform and outscale the simple
version.......It's generally a good idea to use several selectors, mixing fine
grained moves and course grained moves:...
While only one subjectTeacher may be allocated to Period, the solver must temporarily break such a constraint to discover that swapping two certain Period allocations lead to a better solution. A swap move "removes this brick wall" between those two states.
So a swap move can help lead to better solutions much faster.
Cons
A subjectTeacher have only a subset of Periods to which they may be assigned. So finding intersecting (common) hours between any two subjectTeachers is a bit tough (but doable in an elegant way: Good algorithm/technique to find overlapping values from objects' properties? ) .
Will it only give me only small gains in time and optimality?
I am also worried about crazy interactions having two kinds of moves may cause, leading to getting stuck at a bad solution.
如果你对这篇内容有疑问，欢迎到本站社区发帖提问 参与讨论，获取更多帮助，或者扫码二维码加入 Web 技术交流群。
绑定邮箱获取回复消息
由于您还没有绑定你的真实邮箱，如果其他用户或者作者回复了您的评论，将不能在第一时间通知您！
发布评论
评论（1）
互换动作至关重要。
考虑将 2 门课程分配到已满的房间。如果没有交换，就必须打破硬性约束，将 1 门课程移动到冲突的房间，并选择该移动作为步骤（这不太可能）。
您可以使用内置的通用交换 MoveFactory。如果您自己编写，则当您将任何一方移动到不符合条件的时间段时，您可以说交换移动 isDoable() false。
Swap moves are crucial.
Consider 2 courses assigned to a room which is fully booked. Without swapping, it would have to break a hard constraint to move 1 course to a conflicted room and chose that move as the step (which is unlikely).
You can use the build-in generic swap MoveFactory. If you write your own, you can say the swap move isDoable() false when your moving either sides to an ineligible period.