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diff --git a/Practical2/report/future-work.tex b/Practical2/report/future-work.tex new file mode 100644 index 0000000..3ab8978 --- /dev/null +++ b/Practical2/report/future-work.tex @@ -0,0 +1,7 @@ +\section{Future work} +\label{sec:future-work} + +This paper discusses an algorithm to find the minimal sum of rounded sums of a particular sequence. A different task would be to also find the partitioning into sublists that gives this minimal sum. Given the two-dimensional array with $G_p^k$ values this shouldn't be too difficult; it is obviously feasible in $\pazocal O(k\cdot|\bar a|)$ given that table. However, perhaps there are more efficient solutions to this? + +More generally: the algorithm discussed in this report is probably not the most efficient. In particular, I'm wondering if it is really necessary to loop over $0\le i<p$ in line \ref{alg:optimised:line:recurrence} of \autoref{alg:maximum-profit-optimised}, and if it isn't possible to start $i$ higher in some cases. This would probably mean storing some extra data in the main loop of \autoref{alg:maximum-profit-optimised}. + |