Development of Evolutionary Systems Based on Quantum Petri Nets

Tiberiu Stefan Letia (), Elenita Maria Durla-Pasca, Dahlia Al-Janabi and Octavian Petru Cuibus
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Tiberiu Stefan Letia: Department of Automation, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
Elenita Maria Durla-Pasca: Department of Automation, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
Dahlia Al-Janabi: Department of Automation, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania
Octavian Petru Cuibus: Department of Automation, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania

Mathematics, 2022, vol. 10, issue 23, 1-34

Abstract: Evolutionary systems (ES) include software applications that solve problems using heuristic methods instead of the deterministic ones. The classical computing used for ES development involves random methods to improve different kinds of genomes. The mappings of these genomes lead to individuals that correspond to the searched solutions. The individual evaluations by simulations serve for the improvement of their genotypes. Quantum computations, unlike the classical computations, can describe and simulate a large set of individuals simultaneously. This feature is used to diminish the time for finding the solutions. Quantum Petri Nets (QPNs) can model dynamical systems with probabilistic features that make them appropriate for the development of ES. Some examples of ES applications using the QPNs are given to show the benefits of the current approach. The current research solves quantum evolutionary problems using quantum genetic algorithms conceived and improved based on QPN. They were tested on a dynamic system using a Quantum Discrete Controlled Walker (QDCW).

Keywords: quantum computing; genetic algorithms; Petri nets; quantum Petri nets; software development, analysis and verification (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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