Military Operations Research: Quantitative Decision Making (International Series in Operations Research & Management Science) Review

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(More customer reviews)Jaiswal provides the most recent land power-focused military operations research volume. He provides a basic survey of the field, beginning with a very brief discussion of the origins of OR in the military. His topics include search and detection, military simulation, cost effectiveness analysis, optimization, the Analytic Hierarchy Process, Lanchester equations, and a quantified approach to intelligence analysis. The reader should be aware that his coverage of various specific military simulation models is a bit dated, as one should expect in a book, and limited in scope. Beyond that topic, his treatment is broad and therefore less sensitive to the passage of time. The book is a survey, so depth of treatment is not present. But it fills the intended role of pulling together disparate topics of land-based military OR. It also provides some perspective on non NATO defense issues. It must be challenging to decide what to exclude, but surprisingly there is no coverage of network flows, queuing theory, decision analysis, or game theory which have clear military applications. The focus is also on operations rather than the logistics of military analysis.

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The field of Operations Research (OR) grew out of World War IIoperations to improve the effectiveness of newly introduced weaponsand equipment, and to solve logistical problems for the war effort.Since its beginnings, OR has rapidly become a robust set ofdecision-making methodologies widely used in business, engineering,and governmental sectors. Nevertheless, many of OR's military anddefense contributions have remained confined to classified reports.This book is a systematic, state-of-the-art treatment of militaryoperations research (MOR). It has been written for those interested inlearning about the applications of OR techniques to military problems,and within these discussions theoretical concepts needed for analysisof military issues are presented. The book examines issues that relateto both tactical and strategic levels. Several examples have beensolved in each chapter to illustrate the application of the techniquesof MOR to military systems. The data used in these examples arehypothetical. They do not correspond to any existing weapon ormilitary situations. They are used strictly to illustrate anapplication of MOR in defense decision-making.

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Modeling Dynamic Climate Systems (With CD-ROM) Review

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(More customer reviews)This book aims to teach about climate modeling while presenting some fundamentals of atmospheric physics by providing numerous STELLA models ranging from a simple stability model of a leaky bucket to much more complex (and relevant) models for Rossby waves and El Nino. Though the models are not "rigorous", they are intended to show how simplifications can enhance understanding and how some simplifications meet the goals of the model while other times simplifications miss important aspects for accurate models.
For those who are looking for sophisticated programing and modeling approaches, they are sure to be disappointed. However, for those who are either trying to learn or teach basics of climate modeling to those with limited mathematical expertise or teaching students with such limited experience, this book will prove quite useful. The approximately 40 STELLA models included with the book guide the reader to an intuitive understanding of an Earth system approach of atmospheric science. I plan to use a number of examples with a group of students who have only a simple calculus background. Though the text has a 2001 copywrite and the CD-ROM was intended for an earlier version of STELLA, I found that the models could be translated to the newest versions of STELLA on a Macintosh through a fairly simple manipulations and help from software updates provided by High Performance Systems. The text would be useful for junior level classes in atmospheric science aimed at students in environmental science programs. It would be less useful for those with strong math skills majoring in a rigorous atmospheric science sequence, though it could provide such students with a much better conceptual understanding than they might receive in a more mathematically sophisticated class.

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In the process of building and using models to comprehend the dynamics of the atmosphere, ocean and climate, the reader will learn how the different components of climate systems function, interact with each other, and vary over time. Topics include the stability of climate, Earths energy balance, parcel dynamics in the atmosphere, the mechanisms of heat transport in the climate system, and mechanisms of climate variability. Special attention is given to the effects of climate change. The book is accompanied by a cross-platform CD-ROM containing models and a run-time version of STELLA modeling software.

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Modeling for Learning Organizations (System Dynamics Series) Review

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(More customer reviews)"Modeling for Learning Organizations" builds off of the extensive experience of top professors and consultants using the SD tools to test strategies and build an understanding of firm and industry dynamics.
"Modeling" also includes a section overviewing the various simulation software packages available to modelers. Though developers like High-Performance Systems, Vensim, Pugh-Roberts, and PowerSim have made product enhancements to date, the sections from each company provide a great introduction to what is out there how each package can be applied.
The most valuable aspect of the book is probably in the case studies and methodological explorations of several authors. A number of key insights are offered as authors reflect upon the successes and shortcoming of the methods each chose to use to explore and develop models in a variety of business and public environments.
This is definitely a must have for any SD library.

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Conventional wisdom says that we can learn from our errors, but errors in the business world can be prohibitively costly. To truly understand how complex business organizations function requires different tools than most managers have been given. Yet managers need methods to understand how their organization works in order to test policies, discover flaws in thinking, and find the hidden leveragepoints within the complex systems they manage. Through a system simulation, the dynamics of the whole system, not just the individual parts, becomes apparent. The outcome of current and future situations becomes possible to predict and with this information, managers can focus on the changes that need to be made.The distinguished contributors to Modeling for Learning Organizations include Jay W. Forrester, Peter Senge, and Arie De Geus. You will learn about leading applications such as:
Shell's work on modeling the oil producers.
The Management Flight Simulator, a computer-based case learning environment pioneered by John Sterman and others at MIT
The landmark Claims Learning Laboratory at Hanover Insurancecompanies.
For managers, professionals, academicians, and everyone who recognizes the profound implications of modeling, this book is an excellent resource. It offers a broad understanding of the modeling process, discusses a multitude of case studies, and provides a review of the most recent simulation software.

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Systems Science and Modeling for Ecological Economics Review

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(More customer reviews)If you did not do modeling before and have no idea where to start from - this book is for you. It is well written and it is fun!
I had to do some modeling for a project that I have been working on. At that moment I did not have much experience in modeling, especially in modeling coupled economic and natural systems. I was looking for a good guide in ecological economic modeling but could not find anything user-friendly and interdisciplinary. I came across the web-course by Dr. Voinov and started it. The book is a great addition to the course. The web-course as well as this textbook lead you through the essential steps of model design and implementation, introduce you to main challenges and ways to resolve them, and give you some great illustrations from practical applications of ecological economics. I especially like that it provides not only the theory of modeling for ecological economics but also discusses software tools and gives you hands on experience with the exercises. I was very excited to see that the textbook is out there now. Enjoy!


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Modeling is a key component to sciences from mathematics to life science, including environmental and ecological studies. By looking at the underlying concepts of the software, we can make sure that we build mathematically feasible models and that we get the most out of the data and information that we have. This book shows how models can be analyzed using simple math and software to generate meaningful qualitative descriptions of system dynamics. This book shows that even without a full analytical, mathematically rigorous analysis of the equations, there may be ways to derive some qualitative understanding of general behavior of a system. By relating some of the modeling approaches and systems theory to real world examples the book illustrates how these approaches can help understand concepts such as sustainability, peak oil, adaptive management, optimal harvest and other practical applications. * Relates modeling approaches and systems theory to real world examples * Teaches students to build mathematically feasible models and get the most of our the data and information available* Wide range of applications in hydrology, population dynamics, market cycles, sustainability theory, management, and more

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Modeling and Simulation of Dynamic Systems Review

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(More customer reviews)I have taken the Modeling course at UT Arlington with Dr. Woods (the author), the book covers modeling techniques for Electrical, mechanical, heat tranfer..systems. it has a practical review of differenitial equations. Also has Practical simulation information. and it is great to keep as a reference.

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This book reflects the state-of-the-art and current trends in modeling and simulation. The book provides comprehensive coverage of 1) the modeling techniques of the major types of dynamic engineering systems, 2) the solution techniques for the resulting differential equations for linear and nonlinear systems, and 3) the attendant mathematical procedures related to the presentation of dynamic systems and determination of their time and frequency response characteristics. It explains in detail how to select all of the system component parameter values for static and dynamic performance specifications and limits. For anyone interested in systems dynamics, modeling, and interdisciplinary systems.

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Modeling of Dynamic Systems Review

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(More customer reviews)I've been reading this and the book is very inspiring. It has so far given me a good insight on modeling of systems and system control. I Highly recommend this book!

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Written by a recognizedauthority in the field of identification andcontrol, this book draws together into a singlevolume the important aspects of systemidentification AND physical modelling. KEYTOPICS: Explores techniques used to constructmathematical models of systems based on knowledgefrom physics, chemistry, biology, etc. (e.g.,techniques with so called bond-graphs, as wellthose which use computer algebra for the modelingwork). Explains system identification techniquesused to infer knowledge about the behavior ofdynamic systems based on observations of thevarious input and output signals that areavailable for measurement. Shows how both types oftechniques need to be applied in any givenpractical modeling situation. Considersapplications, primarily simulation. For practicing engineers who are faced withproblems of modeling.

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System Modeling in Cellular Biology: From Concepts to Nuts and Bolts (Bradford Books) Review

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(More customer reviews)I'm torn between giving this book 3 or 4 stars. On one hand, it is enjoyable to read and a great value for Amazon's discounted price. On the other hand, the book tries to tackle many modeling techniques at once; I often found myself wishing for more complete descriptions than were provided.
The first section introduces basic concepts of mathematical modeling and considers structures and behaviors characteristic of biological models: The text opens with a discussion of the compromise between model scope and informativeness. Trade-offs of biological robustness and complexity are discussed. Modularity is explored as a unifying property of biological systems.
The next section discusses a range of mathematical modeling frameworks. Bayesian logic is introduced as a means to discriminate among competing models (hypotheses) of biological systems. Quasi-steady state stoichiometric methods, non-linear ODEs, PDEs, and stochastic methods are each given a chapter. Biological network topology is also discussed. While the topics are presented well (some better than others), many (especially the topology and PDE chapters) would benefit from more extensive coverage and mathematical background. The toy model examples are also very simplistic; I would have liked to see discussion of special considerations for higher-dimensional systems.
The third section was the most useful for me and at the same time the most frustrating. It discusses practical issues: experimental data collection, model identification, parameter estimation, and control theory. There is a chapter on gene regulatory systems (think BioBricks or Uri Alon's work) and a brief discussion of multi-scale (cellular/tissue/organ) models. These practical issues - the 'nuts and bolts' of the title - were exactly what I hoped to learn about. However, the coverage is only superficial. I often found myself digging up references to clarify questions which (I felt) should have been addressed in the text.
The final section addresses computing. Algorithm complexity and machine representation of models are informally described. I would have liked to see model identification and parameter estimation covered much more thoroughly - these can be computationally intensive for large models.Runge-Kutta ODE algorithms and stochastic algorithms (Gillespie, tau-leaping, and Langevin) are discussed and computational challenges (e.g., stiffness) are detailed. The book ends with a description of system biology markup language (SBML) and a list of current (as of 2006) open source modeling tools.
I would recommend this books to biological modelers who wish to get a taste of other modeling approaches outside their own specialty. Math students coming into biological projects might also benefit from the introduction to the field. However, the lack of a mathematical review section might leave pure-biology students confused unless they consult dedicated math or modeling texts.
A complete table of contents may be found at The MIT Press website.

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Research in systems biology requires the collaboration of researchersfrom diverse backgrounds, including biology, computer science, mathematics,statistics, physics, and biochemistry. These collaborations, necessary because ofthe enormous breadth of background needed for research in this field, can behindered by differing understandings of the limitations and applicability oftechniques and concerns from different disciplines. This comprehensive introductionand overview of system modeling in biology makes the relevant background materialfrom all pertinent fields accessible to researchers with different backgrounds.Theemerging area of systems level modeling in cellular biology has lacked a criticaland thorough overview. This book fills that gap. It is the first to provide thenecessary critical comparison of concepts and approaches, with an emphasis on theirpossible applications. It presents key concepts and their theoretical background,including the concepts of robustness and modularity and their exploitation to studybiological systems; the best-known modeling approaches, and their advantages anddisadvantages; lessons from the application of mathematical models to the study ofcellular biology; and available modeling tools and datasets, along with theircomputational limitations.

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Modeling and Analysis of Dynamic Systems Review

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(More customer reviews)I had to buy this book for my last semester in electrical engineering. It is a good choice as an introduction to mathematical tools used in representation and analysis of dynamic systems, electrical or mecanical.
First, there are a few chapters about basic notions of dynamic (translational and rotational. You can pass this part quickly if you had a few mechanic classes, because it is just to show the good way to represent systems in modeling. Next, a good explanation of state variable modeling, transfert function, linear vs non linear equations, etc, is well written, with good examples, without too advanced maths. If you have learned basic notions in calculus and linear algebra, you can follow the text pretty easily.

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The book presents the methodology applicable to the modeling and analysis of a variety of dynamic systems, regardless of their physical origin. It includes detailed modeling of mechanical, electrical, electro-mechanical, thermal, and fluid systems. Models are developed in the form of state-variable equations, input-output differential equations, transfer functions, and block diagrams. The Laplace-transform is used for analytical solutions. Computer solutions are based on MATLAB and Simulink.

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Modeling the Environment, Second Edition Review

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(More customer reviews)A highly readable introduction to environmental modeling. What distinguishes the book from other environmental science and environmental modeling works is its interdisciplinary treatment. In particular, the models integrate the physical world and the world of human behavior. Far too many environmental models fail to close the feedbacks between human behavior and the state of the environment, instead taking waste inputs or resource use as exogenous. This book helps students learn to model human behavior (social and economic) as an integral part of the ecological system. The models and software mean the book encourages active learning, and enable students to explore important issues on their own if they choose.

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Modeling the Environment was the first textbook in an emerging field-the modeling techniques that allow managers and researchers to see in advance the consequences of actions and policies in environmental management. This new edition brings the book thoroughly up to date and reaffirms its status as the leading introductory text on the subject. System dynamics is one of the most widely known and widely used methods of modeling. The fundamental principles of this approach are demonstrated here with a wide range of examples, including geo-hydrology, population biology, epidemiology and economics. The applications demonstrate the transferability of the systems approach across disciplines, across spatial scales, and across time scales. All of the models are implemented with stock and flow software programs such as Stella and Vensim. These programs are easy and fun to learn, and they allow students to develop realistic models within the first few weeks of a college course. System dynamics has emerged as the most common approach in collaborative projects to address environmental problems. The stock and flow structures and the emphasis on feedback control provide a common language that is understood by scientists from many disciplines. Although the interdisciplinary approach described here is widely used in practice, there are few books to aid instruction. Modeling the Environment meets the urgent need for instructional materials in interdisciplinary modeling of environmental systems.

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Business Dynamics: Systems Thinking and Modeling for a Complex World with CD-ROM Review

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(More customer reviews)The field of system dynamics was created in 1956 under the leadership of MIT Professor Jay W. Forrester to evaluate how alternative policies affect growth, stability, fluctuation, and changing behavior in corporations, cities, and countries. Forrester founded the System Dynamics Program in the Alfred P. Sloan School of Management at MIT. John Sterman is currently Director of the System Dynamics Group at MIT.
This text is a summary of the wisdom and knowledge gathered over more than twenty years of research dedicated to the study of practical methods for systems thinking and the dynamic modeling of complex systems. It is well written, easy to understand, and worthy of serious consideration.
I believe the text is destined to become a classic. It is written in a straightforward style and does not require prerequisite knowledge of higher mathematics. Indeed, in the author's words, "one of the strengths of the text is the way it presents system dynamics with a minimum of mathematical formalism. The goal is to develop the reader's intuition and conceptual understanding, without sacrificing the rigor of the scientific method." This goal is achieved well.
The text opens with a succinct and well organized description of approaches to the study of complex systems. It develops a set of principles for successful use of systems dynamics and provides well-written overviews of the Modeling Process and dynamic systems.
It covers the construction of causal loop diagrams and describes their application in a variety of business and engineering examples.
This is one of the best texts in its field for upper division undergraduate courses and graduate programs. It will be useful to many in business, engineering, and science.

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The leading authority on system dynamics explains this approach to organizational problem solving, emphasizing simulation models to understand issues such as fluctuating sales, market growth and stagnation, the reliability of forecasts and the rationality of business decision-making. The CD includes modeling software from Vensim, ithink, and PowerSim.

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Excel Data Analysis: Modeling and Simulation Review

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(More customer reviews)I was a graduate student of Professor Guerrero at The College of William and Mary and have to recommend this book. For those unfortunates who did not have him as an instructor, this is a book that gives you the experience of spending time with him in the classroom. The practical application of Excel as a modeling and simulation tool is delivered in a conversational style that engages the reader and occasionally generates a chuckle. Yes, a chuckle in a text that includes the words Excel, Modeling and Simulation in the title. However, inbetween the chuckles is solid theory and application. It's a clever text.
I would recommend this book if only for the discussion of the feng shui of worksheet development - as users, we sometimes don't think through the design of the excel workbook. We build and link, build and link, build and link...
So, Senior Brain, I put my workbook in your hands...

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This book is written for the students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills-Data Analysis, Business Modeling, and Simulation of Complex Problems. The focus of the book is clearly on analysis of problems for decision making, yet detailed explanations regarding how to use Excel tools are provided. After many years of teaching and consulting, it is abundantly clear to me that for most students, a good example is worth its weight in gold. This book contains many excellent examples in each chapter, some simple and others more complex, and there is an abundance of exhibits to guide the student through the maze of steps necessary for each analysis.The content is quite diverse: data presentation - the Feng Shui of spreadsheets, effective communication and collaboration, data preparation - import, scrub, manipulate data, data analysis - statistical methods: descriptive, inferential, and predictive, Design of Experiments, modeling - deterministic, probabilistic, What-if, Scenarios, simulation - quantifying uncertainty, Monte Carlo Simulation, optimization - constrained, Linear Programming, non-linear models, Goal Seek.Couple these features with detailed discussions of how to realistically organize and extract insight from complex problems, and I believe you have a unique educational combination in one book.

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The Art of Modeling Dynamic Systems: Forecasting for Chaos, Randomness and Determinism (Dover Books on Mathematics) Review

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(More customer reviews)
I find myself agreeing with all the comments made so far.
It's not too common to find a book that is able to describe in simple terms, such a large and diverse range of mathematical tools.
The author uses a framework - to tie together tools used in describing and handling deterministic, semi deterministic, and stochastic systems. For an example of Deterministic, try ODE's (ordinary differential equations), for semi deterministic - try Periodic but noisy wave-forms (some stock prices), and finally Stochastic - Random looking waveforms that have underlying patterns that can be described using either using Chaotic indicators (Hurst, Liapunov ) or probability type descriptors.
This book is the kind of thing you needed to help steer you through those dry mathematical books that are divorced from reality - A sort of classification system for deciphering what kind of gunpowder was used in those display's of intellectual fireworks from the tops of ivory towers. Kinda "So thats what all that maths means, but in plain english".
A depth of understanding, for practical application, without intellectual egotism and opaqueness. (But then maybe I'm just a bit thick ... :)
I'd tend to call this book as an equivalent to the Rosetta Stone for the maths of dynamical systems.
You may not use it directly - but you will benefit and grow in understanding from its' plain and simple sign posts along your journey.
It has its place on my book shelf.

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This text demonstrates the roles of statistical methods, coordinate transformations, and mathematical analysis in mapping complex, unpredictable dynamical systems. Written by a well-known authority in the field, it employs practical examples and analogies, rather than theorems and proofs, to characterize the benefits and limitations of modeling tools. 1991 edition.

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