Proceedings of the First International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’16) pp 249-255 | Cite as
Hybrid Bioinspired Search for Schematic Design
Abstract
The paper deals with the one of the most important problem for schematic design of electronic computing equipment—parametric optimization. Due to the high complexity of this problem, the authors suggest a hybrid bioinspired search based on algorithms inspired by natural systems. The paper contains description and formulation of the parametric optimization problem. The suggested architecture is based on the multi-population genetic algorithm (GA). This approach differs from other search methods because search process is divided into two levels and at each level there are used different algorithms. So, it allows the authors to parallelize search process and obtain optimal and quasi-optimal solutions in polynomial time. Computational experiments were carried out on the basis of developed software. As a consequence of tests the authors was convinced that hybrid bioinspired search is a promising method for parametric optimization problems solution. Time complexity of developed algorithms is represented as (nlogn) in the best case and O(n3)—in the worst case.
Keywords
Hybrid bioinspired search Schematic design Parametric optimization Bioinspired algorithm Genetic algorithmNotes
Acknowledgments
This research is supported by grants of the Ministry of Education and Science of the Russian Federation, the project # 8.823.2014.
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