Global optimisation is an important area of applied mathematics that has shown fast and growing development during the last few decades, and deals with the optimisation of a function or a set of functions according to some criteria. In this book the authors discuss the theory, developments and applications of global optimisation including: particle swarm optimisation with re-initialisation strategies for continuous global optimisation; particle swarm global optimisation for orbital manoeuvres; float-encoded genetic algorithms used for the inversion processing of well-logging data; particle collision algorithms; classifier-assisted frameworks for computationally expensive optimisation problems; and the cutting box strategy as an algorithmic framework for improving metaheuristics for continuous global optimisation.