threshold of the acceptable sum of penalties for color conflicts in graph complementary edges (rigidity level), a new bound called the relative robustness threshold (RRT) is proposed. In addition to satisfying constraints related to the number of colors and/or a. In opposition to classical GCP defined for the given graph \(<1\). The results of this work are simple models that practitioners may use to design efficient and competent parallel GAs.Ī new formulation of the robust graph coloring problem (RGCP) is proposed. The paper also presents the additional advantages of combining multi- and single-population parallel GAs.
Later, the models are specialized to consider sparse topologies and migration rates that are more likely to be used by practitioners. Two bounding cases of the migration rate and topology are analyzed, and the case that yields good speedups is optimized. The rest of the paper deals with parallel GAs with multiple populations. The simple GA is then parallelized, and its execution time is optimized. As a first step, the paper shows how to size a simple GA to reach a solution of a desired quality. The investigation centers on the sizing of populations, because previous studies show that there is a crucial relation between solution quality and population size.
The goal of this paper is to provide guidelines to choose those parameters rationally. Parallel genetic algorithms (GAs) are complex programs that are controlled by many parameters, which affect their search quality and their efficiency.
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