Global Optimization Theory, Developments and Applications

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.