Quantum inspired meta-heuristic approach for optimization of genetic algorithm

An optimization search technique evaluates the potential solution and frames the better solution by any of its befitting categories such as quantum-based approaches, meta-heuristic-based approaches, and multi-objective-based approaches. The Quantum Inspired Meta-Heuristic (QIMH) Algorithm is a syner...

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Veröffentlicht in:Computers & electrical engineering 2021-09, Vol.94, p.107356, Article 107356
Hauptverfasser: Ganesan, Vithya, Sobhana, M., Anuradha, G., Yellamma, Pachipala, Devi, O. Rama, Prakash, Kolla Bhanu, Naren, J.
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Sprache:eng
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Zusammenfassung:An optimization search technique evaluates the potential solution and frames the better solution by any of its befitting categories such as quantum-based approaches, meta-heuristic-based approaches, and multi-objective-based approaches. The Quantum Inspired Meta-Heuristic (QIMH) Algorithm is a synergistic combination of evolutionary algorithm, quantum computing, meta-heuristic, and multi-objective approaches to solve hard, exhaustive problems, and to get the best optimization. Techniques such as intensification or exploitation and diversification or exploration are useful in analyzing the optimum solution for the QIMH algorithm. The current research with QIMH algorithm provides a methodology for real time corona virus analysis from its prodigious parameters.
ISSN:0045-7906
1879-0755
DOI:10.1016/j.compeleceng.2021.107356