Simulated Evolution based Hybrids for Genetic Algorithm and Tabu Search
نویسندگان
چکیده
In this paper, Simulated Evolution based goodness attributes are incorporated into Tabu Search and Genetic Algorithms to enhance performance as compared to canonical strategies. In TS, the goodness is used in generating the candidate list of neighboring solutions. In GA, allele fitness is used to define a new crossover which significantly improves over traditional recombination strategies. Both these hybrids are used in VLSI cell placement for large circuits for comparison purposes.
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