QEAM: An Approximate Algorithm Using P Systems with Active Membranes

Gexiang Zhang, Jixiang Cheng, Marian Gheorghe, Florentin Ipate, Xueyuan Wang


This paper proposes an approximate optimization approach, called QEAM, which combines a P system with active membranes and a quantum-inspired evolutionary algorithm. QEAM uses the hierarchical arrangement of the compartments and developmental rules of a P system with active membranes, and the objects consisting of quantum-inspired bit individuals, a probabilistic observation and the evolutionary rules designed with quantum-inspired gates to specify the membrane algorithms. A large number of experiments carried out on benchmark instances of satisfiability problem show that QEAM outperforms QEPS (quantum-inspired evolutionary algorithm based on P systems) and its counterpart quantum-inspired evolutionary algorithm.


Membrane computing, active membranes, approximate optimization approach, quantum-inspired evolutionary algorithm; satisfiability problemThis paper proposes an approximate optimization approach, called QEAM, which combines a P system with active membranes

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DOI: https://doi.org/10.15837/ijccc.2015.2.1757

Copyright (c) 2017 Gexiang Zhang, Jixiang Cheng, Marian Gheorghe, Florentin Ipate, Xueyuan Wang

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