3,083 research outputs found
Engineering planar separator algorithms
We consider classical linear-time planar separator
algorithms, determining for a given planar graph a
small subset of the nodes whose removal separates the
graph into two components of similar size. These algorithms
are based upon Planar Separator Theorems, which
guarantee separators of size asymptotically in the
square root of the number of nodes n and remaining
components of size less than 2n/3. In this work, we
present a comprehensive experimental study of the
algorithms applied to a large variety of graphs, where
the main goal is to find separators that do not only
satisfy upper bounds but also possess other desirable
qualities with respect to separator size and component
balance. We propose the usage of fundamental cycles,
whose size is at most twice the diameter of the graph, as planar
separators: For graphs of small diameter the
guaranteed bound is better than the bounds of the classical
algorithms, and it turns out that this simple strategy almost
always outperforms the other algorithms, even for graphs with
large diameter
Engineering Planar Separator Algorithms
We consider classical linear-time planar separator
algorithms, determining for a given planar graph a
small subset of the nodes whose removal separates the
graph into two components of similar size. These algorithms
are based upon Planar Separator Theorems, which
guarantee separators of size asymptotically in the
square root of the number of nodes n and remaining
components of size less than 2n/3. In this work, we
present a comprehensive experimental study of the
algorithms applied to a large variety of graphs, where
the main goal is to find separators that do not only
satisfy upper bounds but also possess other desirable
qualities with respect to separator size and component
balance. We propose the usage of fundamental cycles,
whose size is at most twice the diameter of the graph, as planar
separators: For graphs of small diameter the
guaranteed bound is better than the bounds of the classical
algorithms, and it turns out that this simple strategy almost
always outperforms the other algorithms, even for graphs with
large diameter
Engineering Planar-Separator and Shortest-Path Algorithms
"Algorithm engineering" denotes the process of designing, implementing, testing, analyzing, and refining computational proceedings to improve their performance. We consider three graph problems -- planar separation, single-pair shortest-path routing, and multimodal shortest-path routing -- and conduct a systematic study in order to: classify different kinds of input; draw concrete recommendations for choosing the parameters involved; and identify and tune crucial parts of the algorithm
Advanced Multilevel Node Separator Algorithms
A node separator of a graph is a subset S of the nodes such that removing S
and its incident edges divides the graph into two disconnected components of
about equal size. In this work, we introduce novel algorithms to find small
node separators in large graphs. With focus on solution quality, we introduce
novel flow-based local search algorithms which are integrated in a multilevel
framework. In addition, we transfer techniques successfully used in the graph
partitioning field. This includes the usage of edge ratings tailored to our
problem to guide the graph coarsening algorithm as well as highly localized
local search and iterated multilevel cycles to improve solution quality even
further. Experiments indicate that flow-based local search algorithms on its
own in a multilevel framework are already highly competitive in terms of
separator quality. Adding additional local search algorithms further improves
solution quality. Our strongest configuration almost always outperforms
competing systems while on average computing 10% and 62% smaller separators
than Metis and Scotch, respectively
Coalition structure generation over graphs
We give the analysis of the computational complexity of coalition structure generation over graphs. Given an undirected graph G = (N,E) and a valuation function v : P(N) → R over the subsets of nodes, the problem is to find a partition of N into connected subsets, that maximises the sum of the components values. This problem is generally NP-complete; in particular, it is hard for a defined class of valuation functions which are independent of disconnected members — that is, two nodes have no effect on each others marginal contribution to their vertex separator. Nonetheless, for all such functions we provide bounds on the complexity of coalition structure generation over general and minor free graphs. Our proof is constructive and yields algorithms for solving corresponding instances of the problem. Furthermore, we derive linear time bounds for graphs of bounded treewidth. However, as we show, the problem remains NP-complete for planar graphs, and hence, for any Kk minor free graphs where k ≥ 5. Moreover, a 3-SAT problem with m clauses can be represented by a coalition structure generation problem over a planar graph with O(m2) nodes. Importantly, our hardness result holds for a particular subclass of valuation functions, termed edge sum, where the value of each subset of nodes is simply determined by the sum of given weights of the edges in the induced subgraph
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