TY - EJOU
AU - Wu, Tao
AU - Xie, Lei
AU - Chen, Xi
AU - Ashrafzadeh, Amir Homayoon
AU - Zhang, Shu
TI - A Novel Quantum-Behaved Particle Swarm Optimization Algorithm
T2 - Computers, Materials \& Continua
PY - 2020
VL - 63
IS - 2
SN - 1546-2226
AB - The efficient management of ambulance routing for emergency requests is vital
to save lives when a disaster occurs. Quantum-behaved Particle Swarm Optimization
(QPSO) algorithm is a kind of metaheuristic algorithms applied to deal with the problem of
scheduling. This paper analyzed the motion pattern of particles in a square potential well,
given the position equation of the particles by solving the SchrĂ¶dinger equation and
proposed the Binary Correlation QPSO Algorithm Based on Square Potential Well (BCQSPSO). In this novel algorithm, the intrinsic cognitive link between particlesâ€™ experience
information and group sharing information was created by using normal Copula function.
After that, the control parameters chosen strategy gives through experiments. Finally, the
simulation results of the test functions show that the improved algorithms outperform the
original QPSO algorithm and due to the error gradient information will not be over utilized
in square potential well, the particles are easy to jump out of the local optimum, the BCQSPSO is more suitable to solve the functions with correlative variables.
KW - Ambulance routing problem
KW - quantum-behaved particle swarm optimization
KW - square potential well
KW - convergence
DO - 10.32604/cmc.2020.07478