Improved quantum particle swarm optimization by bloch sphere

Authors:
Yu Du;Haibin Duan;Renjie Liao;Xihua Li
Affiliations:
National Key Laboratory of Science and Technology on Holistic Control, School of Automation Science and Electrical Engineering, Beihang University, Beijing, China;,National Key Laboratory of Science and Technology on Holistic Control, School of Automation Science and Electrical Engineering, Beihang University, Beijing, China;National Key Laboratory of Science and Technology on Holistic Control, School of Automation Science and Electrical Engineering, Beihang University, Beijing, China;National Key Laboratory of Science and Technology on Holistic Control, School of Automation Science and Electrical Engineering, Beihang University, Beijing, China
Venue:
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2010

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Abstract

Quantum Particle Swarm Optimization (QPSO) is a global convergence guaranteed search method which introduces the Quantum theory into the basic Particle Swarm Optimization (PSO) QPSO performs better than normal PSO on several benchmark problems However, QPSO's quantum bit(Qubit) is still in Hilbert space's unit circle with only one variable, so the quantum properties have been undermined to a large extent In this paper, the Bloch Sphere encoding mechanism is adopted into QPSO, which can vividly describe the dynamic behavior of the quantum In this way, the diversity of the swarm can be increased, and the local minima can be effectively avoided The proposed algorithm, named Bloch QPSO (BQPSO), is tested with PID controller parameters optimization problem Experimental results demonstrate that BQPSO has both stronger global search capability and faster convergence speed, and it is feasible and effective in solving some complex optimization problems.