Commit 586d52a2 authored by Michael Keller's avatar Michael Keller
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parent 83003845
This thesis explores two optimization
methods for pixel farming, a
farming method that attempts to utilize
the benefits of intercrop effects within
a single field. By reducing a one dimensional
version of the problem to finding Hamiltonian
Paths, we were able to demonstrate
the NP completeness of the general problem.
Further we develop two methods
for exploring the large search space.
The first method relaxes the pixel
farming problem to a fractional version
and then uses gradient ascent to search
for solutions. The second method,
through the use of a linear program,
is able to determine the optimal
way of swapping multiple crops
at the same time. Iteratively applying
the latter method resulted in an
improvement over the previous
best score for our benchmark.
These results, therefore, demonstrate the improbability
of finding an algorithm that is both
efficient and optimal. Nevertheless,
one of the presented methods offers
slight improvements over the previous
best scores for our benchmark.
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