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2010

A search space "cartography" for guiding graph coloring heuristics

8 years 9 months ago
A search space "cartography" for guiding graph coloring heuristics
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, we introduce the following clustering hypothesis: the high quality solutions are not randomly scattered in the search space, but rather grouped in clusters within spheres of specific diameter. We first provide intuitive evidence for this hypothesis by presenting a projection of a large set of local minima in the 3D space. An experimental confirmation is also presented: we introduce two algorithms that exploit the hypothesis by guiding an underlying Tabu Search (TS) process. The first algorithm (TS-Div) uses a learning process to guide the basic TS process toward as-yet-unvisited spheres. The second algorithm (TS-Int) makes deep investigations within a bounded region by organizing it as a tree-like structure of connected spheres. We experimentally demonstrate that if such a region contains a global optimum, TS-...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
Added 09 Dec 2010
Updated 09 Dec 2010
Type Journal
Year 2010
Where COR
Authors Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
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