Modeling and simulation - WikipediaResearch on socio-technical systems, to which an enterprise, its organization, business processes, and supporting ICT belong, has been witnessing a resurging interest. Many research initiatives have been launched for the development of concepts, methods, and tools for the analysis and design of the enterprise structure, function, and processes, and for identification of actor roles and responsibilities in a consistent manner. One of the main drivers pushing research into this direction is the changing environment in which enterprises are functioning. In view of these trends, adoption of modeling and simulation, as two complementary tools for design, redesign, and improvement of enterprises, is becoming a standard practice. Especially in the face of ever evolving and changing business environment. In this article, we explain the relationship between enterprise, organization, and business processes on the one hand, and the relevance of modeling and simulation as a method in enterprise and organizational study. Unable to display preview.
Modeling and simulation
In the computer application of " Modeling and simulation" a computer is used to build a mathematical model which contains key parameters of the physical model. The mathematical model represents the physical model in virtual form, and conditions are applied that set up the experiment of interest. The simulation starts — i. Simulation technology belongs to the tool set of engineers of all application domains and has been included in the body of knowledge of engineering management. Because the results of a simulation are only as good as the underlying model s , engineers, operators, and analysts must pay particular attention to its construction. To ensure that the results of the simulation are applicable to the real world, the user must understand the assumptions, conceptualizations, and constraints of its implementation. Additionally, models may be updated and improved using results of actual experiments.
Author s : Hiroki Sayama. Complex systems are systems made of a large number of microscopic components interacting with each other in nontrivial ways. Many real-world systems can be understood as complex systems, where critically important information resides in the relationships between the parts and not necessarily within the parts themselves. This textbook offers an accessible yet technically-oriented introduction to the modeling and analysis of complex systems. The topics covered include: fundamentals of modeling, basics of dynamical systems, discrete-time models, continuous-time models, bifurcations, chaos, cellular automata, continuous field models, static networks, dynamic networks, and agent-based models. Most of these topics are discussed in two chapters, one focusing on computational modeling and the other on mathematical analysis. This unique approach provides a comprehensive view of related concepts and techniques, and allows readers and instructors to flexibly choose relevant materials based on their objectives and needs.