Resumen

BALLINAS, Enrique  y  MONTIEL, Óscar. Hybrid Quantum Genetic Algorithm for the 0-1 Knapsack Problem in the IBM Qiskit Simulator. Comp. y Sist. [online]. 2022, vol.26, n.2, pp.725-742.  Epub 10-Mar-2023. ISSN 2007-9737.  https://doi.org/10.13053/cys-26-2-4253.

In this work, a novel Hybrid Quantum Genetic Algorithm (HQGA) for the 0-1 Knapsack Problem (KP) is presented. It is based on quantum computing principles, such as qubits, superposition, and entanglement of states. The HQGA was simulated in the Qiskit simulator. Qiskit simulator is a platform developed by IBM that allows working with quantum computers at the level of circuits, pulses, and algorithms. The performance of HQGA is evaluated in three strongly correlated KP data sets, and computational results are compared with a Quantum-Inspired Evolutionary Algorithm (QIEA), a modified version of a QIEA (QIEA-Q), and a modified version of the HQGA (HQGA-Q). Experimental results demonstrate that the proposed HQGA can obtain the best solutions in all the KP data sets, and performs well on robustness.

Palabras llave : Quantum computing; quantum genetic algorithm; knapsack problem.

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