Solving satisfiability of Boolean circuits
As a practical view of how a local search works, this example delves into circuit
satisfiability, a classical NP-complete problem. It uses a randomization and Monte
Carlo algorithm approach. As seen in Chapter 17, a Monte Carlo algorithm relies on
random choices during its optimization process and isn’t guaranteed to succeed in
its task, although it has a high likelihood of completing the task successfully. The
problem isn’t merely theoretical, though, because it tests how electronic circuits
work, optimizing them by removing circuits that can’t transport electric signals.
Moreover, the solving algorithm sees use in other applications: automatic labeling
on maps and charts, discrete tomography, scheduling with constraints, data clus-
tering into groups, and other problems for which you have to make conflicting
choices.
CHAPTER 18
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