William T. Scherer – författare

This book focuses on systems analysis, broadly defined to also include problem formulation and interpretation of proposed alternatives in terms of the value systems of stakeholders. Therefore, the book is a complement, not a substitute to other books when teaching systems engineering and systems analysis. The nature of problem solving discussed in this book is appropriate to a wide range of systems analyses. Thus the book can be used as a stand-alone book for teaching the analysis of systems. Also unique is the inclusion of broad case studies to stress problem solving issues, making How to Do Systems Analysis a complement to the many fine works in systems engineering available today.

Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research. This text aims to capture the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike.Presented are an array of the latest contemporary tools - math modelling to tabu search to genetic algorithms - that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.

Presents the foundational systemic thinking needed to conceive systems that address complex socio-technical problemsThis book emphasizes the underlying systems analysis components and associated thought processes. The authors describe an approach that is appropriate for complex systems in diverse disciplines complemented by a case-based pedagogy for teaching systems analysis that includes numerous cases that can be used to teach both the art and methods of systems analysis.  Covers the six major phases of systems analysis, as well as goal development, the index of performance, evaluating candidate solutions, managing systems teams, project management, and morePresents the core concepts of a general systems analysis methodologyIntroduces, motivates, and illustrates the case pedagogy as a means of teaching and practicing systems analysis conceptsProvides numerous cases that challenge readers to practice systems thinking and the systems methodologyHow to Do Systems Analysis: Primer and Casebook is a reference for professionals in all fields that need systems analysis, such as telecommunications, transportation, business consulting, financial services, and healthcare. This book also serves as a textbook for undergraduate and graduate students in systems analysis courses in business schools, engineering schools, policy programs, and any course that promotes systems thinking.

Scheduling is a resource allocation problem which exists in virtually every type of organization. Scheduling problems have produced roughly 40 years of research primarily within the OR community. This community has traditionally emphasized mathematical modeling techniques which seek exact solutions to well formulated optimization problems. While this approach produced important results, many contemporary scheduling problems are particularly difficult. Hence, over the last ten years operations researchers interested in scheduling have turned increasingly to more computer intensive and heuristic approaches. At roughly the same time, researchers in AI began to focus their methods on industrial and management science applications. The result of this confluence of fields has been a period of remarkable growth and excitement in scheduling research. Intelligent Scheduling Systems captures the results of a new wave of research at the forefront of scheduling research, of interest to researchers and practitioners alike. Presented are an array of the latest contemporary tools -- math modeling to tabu search to genetic algorithms -- that can assist in operational scheduling and solve difficult scheduling problems. The book presents the most recent research results from both operations research (OR) and artificial intelligence (AI) focusing their efforts on real scheduling problems.