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Computer simulation has developed into a powerful tool for problem solving in a variety of areas, in the sciences as well as in industrial environments. New developments such as parallel simulation techniques will further improve the efficiency of the tool. Decision support systems, either based on mathematical models or on knowledge based expert systems will make computer simulation accessible to more users, and will provide better environments for systems analysis, modeling and simulation. Systems Analysis and Simulation presents the papers accepted for the 3rd International Symposium for Systems Analysis and Simulation held in Berlin (GDR) in September of 1988. The contributions selected for this two-volume set present the state of the art and current trends in computer simulation. Volume I emphasizes the theoretical foundations and the methodology for computer simulation and systems analysis. Volume II presents a variety of applications in fields such as manufacturing, robotics, economics, and biology.
The impetus to publish this handbook dates back to the Berlin Symposium on Systems Analysis and Simulation in 1988. At that time one could state the close relation between the task of analysing complex systems and the development of simulation software tools. The controlling influence of systems research provides systems analysts with powerful simulation tools supporting the modelling process itself as well as the experimental phase with the simulated model. System Analysis by means of such extended simulation tools here is named briefly Computational Systems Analysis. It connects systems theory, numerical mathematics, control and decisions sciences, and application sciences like biology, economy, and others on the base of computer technique to investigate special systems and to find control strategies.
This book contains the lectures given in the International Course "Improving efficiency and reliability in water supply systems", hosted and sponsored by the Menendez Pelayo International University (U.I.M.P.) and co-sponsored by Aguas de Valencia, the British Council and the EC Cornett and Erasmus programmes. The short course took place in Valencia (Spain) in November 1994, with an attendance of more than one hundred delegates. We must not only acknowedge and thank Dr. Joaquin Azagra, as UIMP Director, but also his collaborators D. Luis Moreno and Lidia Lopez for their support in the preparation of the Course and during the course taking place. UIMP sponsorship allowed us to assemble in Valencia an eminent cadre of lecturers coming from all over the world, that covered in an ordered and precise fashion some of the more relevant aspects on efficiency and reliability in water supply systems. We are very thankful to all these leading lecturers for their invaluable cooperation. The publication of this book and the Spanish edition as well, have been made possible thanks to the sponsorship of both Polytechnic University of Valencia througout its Chancellor, Justo Nieto, and Aguas de Valencia throughout its General Director Alvaro Aguirre. We must also thank Kluwer Academic Publishers and especially their Publisher Petra van Steenbergen for her assistance, careful presentation and production of the book.
"This book provides a rigorous and comprehensive coverage of transportation models and planning methods and is a must-have to anyone in the transportation community, including students, teachers, and practitioners." Moshe Ben-Akiva, Massachusetts Institute of Technology.
The present volume contains the papers which were accepted for presentation at the 3rd International Symposium for Systems Analysis and Simulation held in Berlin (GDR), September 12-:-16, 1988. It is already a tradition to meet a broad international community of experts in systems analysis, modelling and simulation at this symposium. This fact shows the requirements for a forum of presentation and discussion of new developments and applications of modelling and simulation in systems analysis. To realize the great interest in this field one has to take into consideration the developed role of computer simulation as a powerful tool of problem solving. More and more areas in sciences and production have been investigated by mathematical models and computer' simulation. Biological sciences and social sciences are even by now influenced by this trend. The model use on the computer has been very much improved in decision support systems. Parallel simulation will provide drastic shortening of computing time. Parallel simulation and model based decision support systems are brought in the focus of international activities. Numerical mathematics, systems theory and control sciences provide with algorithms supporting the modelling process itself based on simulation or analytic methods. Such simulation systems equipped with tools for modelling and graphics for representing results are real model support systems. A new important impact comes from artificial intelligence by knowledge processing. Expert systems may help decision making in case of missing mathematical models. Expert systems may also support teaching and using simulation systems.
Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the “bible” of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: • A first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses. • A second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. • An introduction to simulation as part of a general course in operations research or management science (part of Chaps. 1, 3, 5, 6, and 9).