Efficacy of Different Strategies in Graph Coloring with Parallel Genetic Algorithms - Sangari, Fardin Esmaeeli; Nabahat, Mehrdad (International Journal of Computer Sciences and Engineering, 2014)
In this paper a new parallel genetic algorithm is proposed to observe efficacy of different strategies for k-graph coloring problem. In the algorithm we have applied a coarse-grained model of parallelism, along with two new algorithms for crossover and mutation are represented: FCX and Fmm. these algorithms compared with CEXï¿½s First Fit and Transposi-tion mutation operators. In our experiments, we observed that different strategies what role have in finding solutions. In computer simulations of PGA we used DIMACS benchmark.