An important topic of the book that appears in nearly all examples is the treatment of the uncertainty in dynamic models. The uncertainty is treated by a deterministic way. No statistical properties of uncertain parameters are used. The uncertain parameter is supposed to be constrained, which leads to a corresponding differential inclusion. The numerical results are obtained using the differential inclusion solver. Solutions of the differential inclusions (the reachable sets) are shown graphically. It should be noted that the presented images of the reachable sets have never been shown by other authors.
Stanislaw Raczynski received his master degree (1964) from the Academy of Mining and Metallurgy (AGH, now called Technical University of Krakow) in Krakow Poland, Electrical Engineering Department, his PhD. (1969) and Habilitation degree (1977) from the same Academy, in the area of control theory and optimization methods. In 1964 Dr.Raczynski joined the Institute for Automatics and Industrial Electronics of the Academy of Mining and Metallurgy in Krakow. From 1971 through 1972, he was the head of the Computer Center of the AGH. Between 1973 and 1976 he worked as a researcher in the International Research Group in Moscow, USSR (located in the Institute for Control Problems of the Academy of Sciences of the USSR). The research area was operations research and computer simulation. In 1976 Dr.Raczynski became head of the Systems Analysis Group at the Academy of Mining and Metallurgy in Krakow. From 1980 through 1983 he participated in the activities of the European Workshop on Industrial Computer Systems. Between 1983 and 1986 he was a visiting professor of the National University of Mexico. In 1986 Dr. Raczynski joined the Panamericana University in Mexico City, Engineering Department. His didactic activities include courses on control theory, electronics and computer simulation.
Between 1996 and 2000 and then between 2002 and 2004 Dr. Raczynski had been the International Director of The Society for Computer Simulation. In 2003-2004 is the international co-director of the McLeod Institute for Simulation Sciences (part of The Society for Computer Simulation in San Diego, California). From 1996 up to now he is a member of the National System of Researchers of Mexico. Between 1994 and 2003 Dr. Raczynski was the director of the Mexican Center of the McLeod Institute of Simulation Sciences. He wrote two books on computer simulation and has more than 70 articles and papers published in professional journals and conference proceedings.
The book covers convex analysis, the theory of optimality conditions, duality theory, and numerical methods for solving unconstrained and constrained optimization problems. It addresses not only classical material but also modern topics such as optimality conditions and numerical methods for problems involving nondifferentiable functions, semidefinite programming, metric regularity and stability theory of set-constrained systems, and sensitivity analysis of optimization problems.
Based on a decade's worth of notes the author compiled in successfully teaching the subject, this book will help readers to understand the mathematical foundations of the modern theory and methods of nonlinear optimization and to analyze new problems, develop optimality theory for them, and choose or construct numerical solution methods. It is a must for anyone seriously interested in optimization.
This book is useful to anyone who wants to increase profits within their business, or improve the quality of their family life and the economic area they live in. It is beneficial for undergraduate and graduate students specializing in the fields of Economic Informatics, Economic Cybernetics, Applied Mathematics and Large Information Systems, as well as for professional economists, and employees of state planning and statistical organizations.
Stanislaw Raczynski outlines the considerable and promising research that is being conducted to counter the problems of uncertainty surrounding the methods used to approach these new applications. It aims to stimulate the reader into seeking out new tools for modelling and simulation.Examines the state-of-the-art in recent research into methods of approaching new applications in the field of modelling and simulation Provides an introduction to new modelling tools such as differential inclusions, metric structures in the space of models, semi-discrete events, and use of simulation in parallel optimization techniques Discusses recently developed practical applications: for example the PASION simulation system, stock market simulation, a new fluid dynamics tool, manufacturing simulation and the simulation of social structures Illustrated throughout with a series of case studies
Modelling and Simulation: The Computer Science of Illusion will appeal to academics, postgraduate students, researchers and practitioners in the modelling and simulation of industrial computer systems. It will also be of interest to those using simulation as an auxiliary tool.
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