I have recently started laying the ground work for multi-threaded
solving, but it will probably only be completed by 6.1 (Q3 2013).
The whole difficulty is going parallel without breaking "incremental
score calculation (delta's)".
The scalability gain of delta's is bigger than parallelization.
Combining the 2 will be a major step forward.
That being said, your approach seems to be at a much higher level:
- Some of those ways might work (although the gain might be low)
- Other approaches, such as partitioning  a single solution into
smaller parts per threads, are doomed to fail due to the nature of
 For example: you can't take the cloud balancing problem of 300
processes and 100 computers
and have 10 threads optimally assign 30 processes to 10 computers and
expect to find a global optimal solution.
Further more, once you have serious constraints (such as
machinereassignment's constraint "processes of the same service should
run on computers on distinct locations"),
you can't even optimize 30 processes without knowing how the other 270
processes are assigned.
Op 19-12-12 03:31, 软件0907黄泓 schreef:
I am thinking about realizing the solving process in a multi-thread way,and once a
group of optimal parameters was found by one thread, it was adopted by other theads. Was
it a feasible approach?
with kind regards
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