The scientific research in many engineering fields has been shifting from traditional first-principle-based to data-driven or evidence-based theories. The latter methods may enable better system design, based on more accurate and verifiable information.

This book comprises ten invited expert contributions on the theory and applications of genetic algorithms in a variety of engineering systems. In addition to addressing the simple formulation of GAs, the chapters include original material on the design of evolutionary algorithms for particular engineering applications. Chosen for their experience in the field, the authors are drawn from both academia and industry worldwide, and provide extensive insight into their respective fields. The volume is suitable for researchers and postgraduates who need to be up-to-date with developments in this important subject, as well as practitioners in industry who are eager to find out how to solve their particular real-life problems.

This guide will prove a great help to businesses in providing the pratical advice that will enable them to master the art of logistics so it can be used to their best business advantage.

Parameter estimation is the process of using observations from a system to develop mathematical models that adequately represent the system dynamics. The assumed model consists of a finite set of parameters, the values of which are calculated using estimation techniques. Most of the techniques that exist are based on least-square minimisation of error between the model response and actual system response. However, with the proliferation of highspeed digital computers, elegant and innovative techniques like filter error method, genetic algorithms and artificial neural networks are finding more and more use in parameter estimation problems. Modelling and Parameter Estimation of Dynamic Systems presents a detailed examination of many estimation techniques and modelling problems.

Systems modelling is an essential enabling technique for any systems engineering enterprise. These modelling techniques, in particular the unified modelling language (UML), have been employed widely in the world of software engineering and very successfully in systems engineering for many years. However, in recent years there has been a perceived need for a tailored version of the UML that meets the needs of today's systems engineering professional. This book provides a pragmatic introduction to the systems engineering modelling language, the SysML, aimed at systems engineering practitioners at any level of ability, ranging from students to experts. The theoretical aspects and syntax of SysML are covered and each concept is explained through a number of example applications. The book also discusses the history of the SysML and shows how it has evolved over a number of years. All aspects of the language are covered and are discussed in an independent and frank manner, based on practical experience of applying the SysML in the real world.

The transfer of responsibility for decisions and actions from humans to machines presents difficult problems for all those concerned with new concepts, their development and use. This book gives practical help by discussing the issues in the context of product design, and gives a methodology to solve them.

Up until a few years ago there were many different modelling languages available to software developers. However, this vast array of choice only served to hinder communication and as a result the Unified Modelling Language (UML) was born. Although the UML has its roots firmly in the software world, the benefits of adopting a standard visual notation have been recognised in many other fields, not least of which is the field of systems engineering. This book concentrates on systems-based applications, rather than the traditional software applications that are more usually associated with the UML. Now fully updated to reflect the changes to UML for its version 2.0 release, this new edition has been substantially re-written and includes new material on systems architectures and life cycle management.