8.4. Scalability of Exhaustive Search
Exhaustive Search variants suffer from 2 big scalability issues:
- They scale terribly memory wise.
- They scale horribly performance wise.
As shown in these time spent graphs from the Benchmarker, Brute Force and Branch And Bound both hit a performance scalability wall. For example, on N queens it hits wall at a few dozen queens:
In most use cases, such as Cloud Balancing, the wall appears out of thin air:
Exhaustive Search hits this wall on small datasets already, so in production these optimizations algorithms are mostly useless. Use Construction Heuristics with Local Search instead: those can handle thousands of queens/computers easily.
Throwing hardware at these scalability issues has no noticeable impact. Newer and more hardware are just a drop in the ocean. Moore’s law cannot win against the onslaught of a few more planning entities in the dataset.
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