1 research outputs found
A heuristic approach for dividing graphs into bi-connected components with a size constraint
In this paper we propose a new problem of finding the maximal bi-connected
partitioning of a graph with a size constraint (MBCPG-SC). With the goal of
finding approximate solutions for the MBCPG-SC, a heuristic method is developed
based on the open ear decomposition of graphs. Its essential part is an
adaptation of the breadth first search which makes it possible to grow
bi-connected subgraphs. The proposed randomized algorithm consists of growing
several subgraphs in parallel. The quality of solutions generated in this way
is further improved using a local search which exploits neighboring relations
between the subgraphs. In order to evaluate the performance of the method, an
algorithm for generating pseudo-random unit disc graphs with known optimal
solutions is created. The conducted computational experiments show that the
proposed method frequently manages to find optimal solutions and has an average
error of only a few percent to known optimal solutions. Further, it manages to
find high quality approximate solutions for graphs having up to 10.000 nodes in
reasonable time