Local optima topology for the k-coloring problem
Discrete Applied Mathematics - Special volume: viewpoints on optimization
New methods to color the vertices of a graph
Communications of the ACM
Frozen development in graph coloring
Theoretical Computer Science - Phase transitions in combinatorial problems
Tabu Search
An Experimental Investigation of Iterated Local Search for Coloring Graphs
Proceedings of the Applications of Evolutionary Computing on EvoWorkshops 2002: EvoCOP, EvoIASP, EvoSTIM/EvoPLAN
A New Genetic Local Search Algorithm for Graph Coloring
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Register allocation & spilling via graph coloring
SIGPLAN '82 Proceedings of the 1982 SIGPLAN symposium on Compiler construction
Robust Graph Coloring for Uncertain Supply Chain Management
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences (HICSS'05) - Track 3 - Volume 03
A survey of local search methods for graph coloring
Computers and Operations Research - Anniversary focused issue of computers & operations research on tabu search
Computers and Operations Research
A graph coloring heuristic using partial solutions and a reactive tabu scheme
Computers and Operations Research
An adaptive memory algorithm for the k-coloring problem
Discrete Applied Mathematics
Variable space search for graph coloring
Discrete Applied Mathematics
A Metaheuristic Approach for the Vertex Coloring Problem
INFORMS Journal on Computing
Computers and Operations Research
Coloring large graphs based on independent set extraction
Computers and Operations Research
Proceedings of the 13th annual conference on Genetic and evolutionary computation
An empirical comparison of some approximate methods for graph coloring
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Improving the extraction and expansion method for large graph coloring
Discrete Applied Mathematics
Hi-index | 0.01 |
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-Int does not fail in eventually finding it. This pair of algorithms significantly outperforms the underlying basic TS algorithm; it can even improve some of the best-known solutions ever reported in the literature (e.g. for dsjc1000.9).