Guiding you through the key stages of a simulation project, this textbook provides a comprehensive introduction to the discipline.The book shows you how to develop conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. It takes a non-software specific view and can be used regardless of individual software preferences. Almost all of the techniques described also apply to the use of non-specialist simulation software, such as programming languages and spreadsheets. This edition also details advancements such as hybrid simulation, multiple recursive random number generators and digital twins. A new chapter has also been added on single-use systems, which solidifies the text’s holistic approach to simulation studies. Critical engagement is encouraged through the inclusion of practical case studies and complementary online resources. Each simulation model is accompanied by illustrative examples, comparative discussions and references to promote deeper understanding of each depicted model. Every chapter is bookended by key concept definitions and summaries.Packed full of practical tips that can be immediately employed in any model development cycle - regardless of your knowledge level - Simulation is an ideal textbook for students studying simulation on upper level undergraduate and postgraduate degree courses in Business and Management, Operations Management, Logistics and Supply Chain Management, Computer Science, Engineering, Mathematics and Statistics. The text is also an invaluable resource for practitioners, such as business analysts.

Bringing together an international group of researchers involved in military, business, and health modeling and simulation, Conceptual Modeling for Discrete-Event Simulation presents a comprehensive view of the current state of the art in the field. The book addresses a host of issues, including: What is a conceptual model?How is conceptual modeling performed in general and in specific modeling domains?What is the role of established approaches in conceptual modeling?Each of the book’s six parts focuses on a different aspect of conceptual modeling for simulation. The first section discusses the purpose and requirements of a conceptual model. The next set of chapters provides frameworks and tools for conceptual modeling. The book then describes the use of soft systems methodology for model structuring as well as the application of software engineering methods and tools for model specification. After illustrating how conceptual modeling is adopted in the military and semiconductor manufacturing, the book concludes with a discussion on future research directions.This volume offers a broad, multifaceted account of the field by presenting diverse perspectives on what conceptual modeling entails. It also provides a basis upon which these perspectives can be compared.

The new edition of this successful textbook provides a comprehensive introduction to simulation, foregrounding the topic as an applied problem-solving tool. Guiding readers through the key stages in a simulation project in terms of both the technical requirements and the project management issues surrounding it, the book will enable students to develop appropriate valid conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. The author''s engaging style and authoritative knowledge of the subject make the book as accessible as it is essential, drawing on case studies and complementary online content to encourage a critical engagement with the topic.This is an ideal textbook for those studying on upper level undergraduate and postgraduate degree courses in business and management and MBA programmes, and is a core text for those specialising in operations management. In addition, it is an important text for students taking Simulation modules on engineering, computer science or mathematics degree programmes.New to this Edition:- A practical step-by-step guide to preparing a simple model- Improved cross referencing, navigation and design- Updated referencing and the inclusion of select new case studies- New material available via the companion website- Key concepts, on-page glossary terms and relevant further reading lists for each chapter

Guiding you through the key stages of a simulation project, this textbook provides a comprehensive introduction to the discipline. The book shows you how to develop conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. It takes a non-software specific view and can be used regardless of individual software preferences. Almost all of the techniques described also apply to the use of non-specialist simulation software, such as programming languages and spreadsheets. This edition also details advancements such as hybrid simulation, multiple recursive random number generators and digital twins. A new chapter has also been added on single-use systems, which solidifies the text's holistic approach to simulation studies. Critical engagement is encouraged through the inclusion of practical case studies and complementary online resources. Each simulation model is accompanied by illustrative examples, comparative discussions and references to promote deeper understanding of each depicted model. Every chapter is bookended by key concept definitions and summaries.Packed full of practical tips that can be immediately employed in any model development cycle - regardless of your knowledge level - Simulation is an ideal textbook for students studying simulation on upper level undergraduate and postgraduate degree courses in Business and Management, Operations Management, Logistics and Supply Chain Management, Computer Science, Engineering, Mathematics and Statistics. The text is also an invaluable resource for practitioners, such as business analysts.

Guiding you through the key stages of a simulation project, this textbook provides a comprehensive introduction to the discipline. The book shows you how to develop conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. It takes a non-software specific view and can be used regardless of individual software preferences. Almost all of the techniques described also apply to the use of non-specialist simulation software, such as programming languages and spreadsheets. This edition also details advancements such as hybrid simulation, multiple recursive random number generators and digital twins. A new chapter has also been added on single-use systems, which solidifies the text's holistic approach to simulation studies. Critical engagement is encouraged through the inclusion of practical case studies and complementary online resources. Each simulation model is accompanied by illustrative examples, comparative discussions and references to promote deeper understanding of each depicted model. Every chapter is bookended by key concept definitions and summaries.Packed full of practical tips that can be immediately employed in any model development cycle - regardless of your knowledge level - Simulation is an ideal textbook for students studying simulation on upper level undergraduate and postgraduate degree courses in Business and Management, Operations Management, Logistics and Supply Chain Management, Computer Science, Engineering, Mathematics and Statistics. The text is also an invaluable resource for practitioners, such as business analysts.

Guiding you through the key stages of a simulation project, this textbook provides a comprehensive introduction to the discipline.The book shows you how to develop conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. It takes a non-software specific view and can be used regardless of individual software preferences. Almost all of the techniques described also apply to the use of non-specialist simulation software, such as programming languages and spreadsheets. This edition also details advancements such as hybrid simulation, multiple recursive random number generators and digital twins. A new chapter has also been added on single-use systems, which solidifies the text’s holistic approach to simulation studies. Critical engagement is encouraged through the inclusion of practical case studies and complementary online resources. Each simulation model is accompanied by illustrative examples, comparative discussions and references to promote deeper understanding of each depicted model. Every chapter is bookended by key concept definitions and summaries.Packed full of practical tips that can be immediately employed in any model development cycle - regardless of your knowledge level - Simulation is an ideal textbook for students studying simulation on upper level undergraduate and postgraduate degree courses in Business and Management, Operations Management, Logistics and Supply Chain Management, Computer Science, Engineering, Mathematics and Statistics. The text is also an invaluable resource for practitioners, such as business analysts.

Bringing together an international group of researchers involved in military, business, and health modeling and simulation, Conceptual Modeling for Discrete-Event Simulation presents a comprehensive view of the current state of the art in the field. The book addresses a host of issues, including: What is a conceptual model?How is conceptual modeling performed in general and in specific modeling domains?What is the role of established approaches in conceptual modeling?Each of the book’s six parts focuses on a different aspect of conceptual modeling for simulation. The first section discusses the purpose and requirements of a conceptual model. The next set of chapters provides frameworks and tools for conceptual modeling. The book then describes the use of soft systems methodology for model structuring as well as the application of software engineering methods and tools for model specification. After illustrating how conceptual modeling is adopted in the military and semiconductor manufacturing, the book concludes with a discussion on future research directions.This volume offers a broad, multifaceted account of the field by presenting diverse perspectives on what conceptual modeling entails. It also provides a basis upon which these perspectives can be compared.

Bringing together an international group of researchers involved in military, business, and health modeling and simulation, Conceptual Modeling for Discrete-Event Simulation presents a comprehensive view of the current state of the art in the field. The book addresses a host of issues, including: What is a conceptual model?How is conceptual modelin

Guiding you through the key stages of a simulation project, this textbook provides a comprehensive introduction to the discipline.The book shows you how to develop conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. It takes a non-software specific view and can be used regardless of individual software preferences. Almost all of the techniques described also apply to the use of non-specialist simulation software, such as programming languages and spreadsheets. This edition also details advancements such as hybrid simulation, multiple recursive random number generators and digital twins. A new chapter has also been added on single-use systems, which solidifies the text’s holistic approach to simulation studies. Critical engagement is encouraged through the inclusion of practical case studies and complementary online resources. Each simulation model is accompanied by illustrative examples, comparative discussions and references to promote deeper understanding of each depicted model. Every chapter is bookended by key concept definitions and summaries.Packed full of practical tips that can be immediately employed in any model development cycle - regardless of your knowledge level - Simulation is an ideal textbook for students studying simulation on upper level undergraduate and postgraduate degree courses in Business and Management, Operations Management, Logistics and Supply Chain Management, Computer Science, Engineering, Mathematics and Statistics. The text is also an invaluable resource for practitioners, such as business analysts.

Bringing together an international group of researchers involved in military, business, and health modeling and simulation, Conceptual Modeling for Discrete-Event Simulation presents a comprehensive view of the current state of the art in the field. The book addresses a host of issues, including: What is a conceptual model?How is conceptual modeling performed in general and in specific modeling domains?What is the role of established approaches in conceptual modeling?Each of the book’s six parts focuses on a different aspect of conceptual modeling for simulation. The first section discusses the purpose and requirements of a conceptual model. The next set of chapters provides frameworks and tools for conceptual modeling. The book then describes the use of soft systems methodology for model structuring as well as the application of software engineering methods and tools for model specification. After illustrating how conceptual modeling is adopted in the military and semiconductor manufacturing, the book concludes with a discussion on future research directions.This volume offers a broad, multifaceted account of the field by presenting diverse perspectives on what conceptual modeling entails. It also provides a basis upon which these perspectives can be compared.

The new edition of this successful textbook provides a comprehensive introduction to simulation, foregrounding the topic as an applied problem-solving tool. Guiding readers through the key stages in a simulation project in terms of both the technical requirements and the project management issues surrounding it, the book will enable students to develop appropriate valid conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. The author''s engaging style and authoritative knowledge of the subject make the book as accessible as it is essential, drawing on case studies and complementary online content to encourage a critical engagement with the topic.This is an ideal textbook for those studying on upper level undergraduate and postgraduate degree courses in business and management and MBA programmes, and is a core text for those specialising in operations management. In addition, it is an important text for students taking Simulation modules on engineering, computer science or mathematics degree programmes.New to this Edition:- A practical step-by-step guide to preparing a simple model- Improved cross referencing, navigation and design- Updated referencing and the inclusion of select new case studies- New material available via the companion website- Key concepts, on-page glossary terms and relevant further reading lists for each chapter

Guiding you through the key stages of a simulation project, this textbook provides a comprehensive introduction to the discipline. The book shows you how to develop conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. It takes a non-software specific view and can be used regardless of individual software preferences. Almost all of the techniques described also apply to the use of non-specialist simulation software, such as programming languages and spreadsheets. This edition also details advancements such as hybrid simulation, multiple recursive random number generators and digital twins. A new chapter has also been added on single-use systems, which solidifies the text's holistic approach to simulation studies. Critical engagement is encouraged through the inclusion of practical case studies and complementary online resources. Each simulation model is accompanied by illustrative examples, comparative discussions and references to promote deeper understanding of each depicted model. Every chapter is bookended by key concept definitions and summaries.Packed full of practical tips that can be immediately employed in any model development cycle - regardless of your knowledge level - Simulation is an ideal textbook for students studying simulation on upper level undergraduate and postgraduate degree courses in Business and Management, Operations Management, Logistics and Supply Chain Management, Computer Science, Engineering, Mathematics and Statistics. The text is also an invaluable resource for practitioners, such as business analysts.

Guiding you through the key stages of a simulation project, this textbook provides a comprehensive introduction to the discipline. The book shows you how to develop conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. It takes a non-software specific view and can be used regardless of individual software preferences. Almost all of the techniques described also apply to the use of non-specialist simulation software, such as programming languages and spreadsheets. This edition also details advancements such as hybrid simulation, multiple recursive random number generators and digital twins. A new chapter has also been added on single-use systems, which solidifies the text's holistic approach to simulation studies. Critical engagement is encouraged through the inclusion of practical case studies and complementary online resources. Each simulation model is accompanied by illustrative examples, comparative discussions and references to promote deeper understanding of each depicted model. Every chapter is bookended by key concept definitions and summaries.Packed full of practical tips that can be immediately employed in any model development cycle - regardless of your knowledge level - Simulation is an ideal textbook for students studying simulation on upper level undergraduate and postgraduate degree courses in Business and Management, Operations Management, Logistics and Supply Chain Management, Computer Science, Engineering, Mathematics and Statistics. The text is also an invaluable resource for practitioners, such as business analysts.

Guiding you through the key stages of a simulation project, this textbook provides a comprehensive introduction to the discipline.The book shows you how to develop conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. It takes a non-software specific view and can be used regardless of individual software preferences. Almost all of the techniques described also apply to the use of non-specialist simulation software, such as programming languages and spreadsheets. This edition also details advancements such as hybrid simulation, multiple recursive random number generators and digital twins. A new chapter has also been added on single-use systems, which solidifies the text’s holistic approach to simulation studies. Critical engagement is encouraged through the inclusion of practical case studies and complementary online resources. Each simulation model is accompanied by illustrative examples, comparative discussions and references to promote deeper understanding of each depicted model. Every chapter is bookended by key concept definitions and summaries.Packed full of practical tips that can be immediately employed in any model development cycle - regardless of your knowledge level - Simulation is an ideal textbook for students studying simulation on upper level undergraduate and postgraduate degree courses in Business and Management, Operations Management, Logistics and Supply Chain Management, Computer Science, Engineering, Mathematics and Statistics. The text is also an invaluable resource for practitioners, such as business analysts.

Bringing together an international group of researchers involved in military, business, and health modeling and simulation, Conceptual Modeling for Discrete-Event Simulation presents a comprehensive view of the current state of the art in the field. The book addresses a host of issues, including: What is a conceptual model?How is conceptual modeling performed in general and in specific modeling domains?What is the role of established approaches in conceptual modeling?Each of the book’s six parts focuses on a different aspect of conceptual modeling for simulation. The first section discusses the purpose and requirements of a conceptual model. The next set of chapters provides frameworks and tools for conceptual modeling. The book then describes the use of soft systems methodology for model structuring as well as the application of software engineering methods and tools for model specification. After illustrating how conceptual modeling is adopted in the military and semiconductor manufacturing, the book concludes with a discussion on future research directions.This volume offers a broad, multifaceted account of the field by presenting diverse perspectives on what conceptual modeling entails. It also provides a basis upon which these perspectives can be compared.

Bringing together an international group of researchers involved in military, business, and health modeling and simulation, Conceptual Modeling for Discrete-Event Simulation presents a comprehensive view of the current state of the art in the field. The book addresses a host of issues, including: What is a conceptual model?How is conceptual modelin