A membrane algorithm with quantum-inspired subalgorithms and its application to image processing
Natural Computing: an international journal
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To improve the local search capability of quantum-inspired evolutionary algorithm based on P systems (QEPS), a memetic algorithm based on P systems (MAPS) was proposed. MAPS is a hybrid algorithm combining the hierarchical framework and evolution rules of P systems with real-observation quantum-inspired evolutionary algorithms (rQIEA) and local search methods (LS). In MAPS, rQIEA is employed in elementary membranes to explore the whole solution space and TS is applied inside the skin membrane to search the neighbouring domains of each variable of the best solution obtained. Five complex benchmark functions with 100 dimensions are employed to test the effectiveness of the approach. Experimental results show that MAPS performs better than rQIEA in terms of search ability and stability. In addition, this paper presents the application of membrane algorithms to infinite-impulse response (IIR) digital filter design. The experiments show that MAPS can obtain better digital filter performances than NQGA and GA.