You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This commit was created on GitHub.com and signed with GitHub’s verified signature.
The key has expired.
[2.7.0] - 2021-2-25
Added
Added HybridConstructiveHeuristic, which provides the ability
to use multiple heuristics with a stochastic sampling search,
where a heuristic is chosen from a set of constructive heuristics
at the start of each iteration of the stochastic sampler and used
for all decisions made during that iteration. The class supports the
following strategies for selecting the next heuristic:
Heuristic uniformly at random from among the available heuristics.
Heuristic chosen using a round robin strategy that systematically cycles
over the heuristics.
Heuristic chosen via a weighted random selection process.
Added versions of a few constructive heuristics for
scheduling problems that precompute heuristic values
upon construction of the heuristic. Many of the scheduling
heuristic implementations already do this, where it is
possible to do so, provided the memory and time requirements
for precomputing heuristic values is linear in the number
of jobs. Some heuristics that consider setup times, however,
need quadratic memory if the heuristic is precomputed prior
to running the search. The existing implementations of these
compute the heuristic as it is needed during the search,
which means for a stochastic sampler with many iterations
that the same heuristic values will be computed repeatedly.
We've added versions of these that precompute the heuristic
values so that if your problem is small enough to afford the
quadratic memory, and if you will be running enough iterations
of the stochastic sampler to afford the quadratic time of
this precomputation step, then you can choose to use a
precomputed version.
A scheduling heuristic, SmallestSetupPrecompute, which is
a version of SmallestSetup, but which precomputes a table
of heuristic values to avoid recomputing the same heuristic
values repeatedly across multiple iterations of a stochastic
sampling search.
A scheduling heuristic, ShortestProcessingPlusSetupTimePrecompute, which is
a version of ShortestProcessingPlusSetupTime, but which precomputes a table
of heuristic values to avoid recomputing the same heuristic
values repeatedly across multiple iterations of a stochastic
sampling search.
A scheduling heuristic, WeightedShortestProcessingPlusSetupTimePrecompute, which is
a version of WeightedShortestProcessingPlusSetupTime, but which precomputes a table
of heuristic values to avoid recomputing the same heuristic
values repeatedly across multiple iterations of a stochastic
sampling search.