The interaction of mathematical and computational modeling with practical design applications is well known for its early successes in the use and development of linear programming, and its role in logistical planning in the period around World War II. This field has grown in areas of application in the physical sciences, the social sciences, and engineering, and in the statistical analysis of the 2012 US general election by leading journalistic centers. At the same time, the subjects of mathematical modeling, computation, and software design and interfaces have evolved as well. One interesting area in physical science and engineering modeling associated with optimization modeling is its application to space engineering. This book presents a collection of such modeling applied to a wide variety of problems related to design, optimal analysis, computational fluid dynamics (CFD), and issues of optimization of payload and related problems that arise from both manned and unmanned missions by the National Aeronautics and Space Administration’s (NASA’s) International Space Station (ISS) and the European Space Agency (ESA).

The book consists of 16 chapters on applications, software development, and mathematical and numerical methods, beginning with an introductory chapter that reflects the book’s range: “Model Development and Optimization for Space Engineering: Concepts, Tools, Applications, and Perspectives.” Subsequent chapters in the first half explore topics from optimal control theory and applications, collocation methods, the flying of satellites, and software for solving nonlinear programming problems. The book also addresses the global optimization of applications using differential algebra. The second half deals with more specific applications, including mixed integer linear programming (MILP) modeling for traffic logistics at the ISS, on-board storage optimization, the design of hybrid rocket engines, and the optimization of low-energy transfers.

The book is not without some shortcomings. In particular, the authors use a number of acronyms that are not adequately or consistently explained. This may be in part because the reader is expected to be an engineer and thus familiar with the terminology, or it may be that copyediting was not consistently done across all the chapters.

This book is targeted at practitioners of mathematical and computational optimization methods and/or engineering applications. In this respect, the book provides a state-of-the-art contribution that covers its topics well.