Diaz:
-- 1.1.2: progress was made not only by means of new algorithms, but also
- due to better data structures
-- 1.4.2: full list of authors
-- 1.4.20: proof -> comment
- 2: simplify, remove proof sketches
- 2.3: mention radix sorting in linear time
- 2.5.24: skip proof
Finding Minimum Spanning Trees. SIAM J. on Comp. 5(4) (1976) pp.
724-742. who gave a linear time algorithm for planar graphs, extended by
Tarjan in 1983 to proper minor closed classes (both quoted by Gustedt).
+ [XXX: Cannot get the paper.]
- In 3.1.12 and 3.1.16, you should make explicit the dependence of the
running time with respect, for instance, to the Hadwiger number of the
graph or to the maximal density nabla(G) of a minor of the graph, as
number = "2007/5",
type = "Tech Report"
}
+
+@article{ florek:liaison,
+ title={{Sur la liaison et la division des points d'un ensemble fini}},
+ author={Florek, K. and {\L}ukaszewicz, J. and Perkal, H. and Steinhaus, H. and Zubrzycki, S.},
+ journal={Colloquium Mathematicum},
+ volume={2},
+ pages={282--285},
+ year={1951}
+}
from the $\O(m\timesbeta(m,n))$ time algorithm by Fredman and Tarjan \cite{ft:fibonacci},
over algorithms with inverse-Ackermann type complexity by Chazelle \cite{chazelle:ackermann}
and Pettie \cite{pettie:ackermann}, to an~algorithm by Pettie \cite{pettie:optimal}
-whose time complexity is provably optimal.
+whose time complexity is provably optimal. Frequently, the most important ingredients
+were advances in data structures used to represent the graph.
In the upcoming chapters, we will explore this colorful universe of MST algorithms.
We will meet the canonical works of the classics, the clever ideas of their successors,
the \df{neighboring edges} of the tree). We add all such edges to the forest and
proceed with the next iteration.
-\algn{Bor\o{u}vka \cite{boruvka:ojistem}, Choquet \cite{choquet:mst}, Sollin \cite{sollin:mst}, and others}
+\algn{Bor\o{u}vka \cite{boruvka:ojistem}, Choquet \cite{choquet:mst}, Florek et al.~\cite{florek:liaison}, Sollin \cite{sollin:mst}}
\algo
\algin A~graph~$G$ with an edge comparison oracle.
\:$T\=$ a forest consisting of vertices of~$G$ and no edges.
the same component. If they do not, addition of this edge connects both components into one,
so we perform $\<Union>(u,v)$ to merge the equivalence classes.
-Tarjan has shown that there is a~data structure for the DSU problem
+Tarjan \cite{tarjan:setunion} has shown that there is a~data structure for the DSU problem
of surprising efficiency:
\thmn{Disjoint Set Union, Tarjan \cite{tarjan:setunion}}\id{dfu}%
comprising of $n$~\<Union>s intermixed with $m\ge n$~\<Find>s can be processed in time
$\O(m\timesalpha(m,n))$, where $\alpha(m,n)$ is a~certain inverse of the Ackermann's function
(see Definition \ref{ackerinv}).
-
-\proof
-See \cite{tarjan:setunion}.
\qed
-This completes the following theorem:
+Using this data structure, we get the following bound:
\thm\id{kruskal}%
The Kruskal's algorithm finds the MST of a given graph in time $\O(m\log n)$.