Although the particle swarm optimisation (PSO) algorithm requires relatively few parameters and is computationally simple and easy to implement, it is not a globally convergent algorithm. In Particle Swarm Optimisation: Classical and Quantum Perspectives, the authors introduce their concept of quantum-behaved particles inspired by quantum mechanics, which leads to the quantum-behaved particle swarm optimisation (QPSO) algorithm. This globally convergent algorithm has fewer parameters, a faster convergence rate, and stronger searchability for complex problems.

This book explains how to solve differential equations using novel splitting methods based on iterative schemes. It covers differential equations of parabolic and hyperbolic equation systems occurring in multiphysics and multiscale problems. The author analyzes the convergence of iterative splitting methods with respect to the bounded and unbounded operators. Practical results are presented in the test examples and real-life problems, with a focus on the computational benefit in fluid dynamics, heat transfer, and electromagnetics. A CD-ROM includes MATLABA(R) and other software code.