Simulation Books

I had to learn formZ for my profession and I've gone to great lengths to do so. I had already taken two courses from different instructors and I was still feeling very unstable and was about to start a new job where I really needed the skills. Stressed-out and feeling at a loss, I did a search on the web and found this book for the new 4.0. While I already had a great understanding of the program, this book showed me so many ways to do things I had not yet been taught and I was able to do it on my own. The information is clearly laid out and easy to understand. Icons let you reference exactly where to go but the best part was the tutorials. I have not been able to find in any class or supporting material that came with the software, tutorials that let you practice. This was the most helpful as it's never enough to just know what everything does. You need to implement the info. This book saved my life (and probably my career!!)

Even though I did not follow the books step by step classroom exercises, but used it as a reference on "how to" questions for my own projects, this book was essential for me in the creation of several designs at a very satisfying level. The explanations are well written and logical. Still at a beginners level, I was surprised at how much I had learned over the course of 2 weeks focussing on form Z (for at least several hours per day). Render Zone is also well covered in the book and it allowed me to create great and surprisingly realistic looking renderings that I was able to use for client presentations.

Clearly written from an architectural standpoint, the only thing the book lacks is addressing some of the specific needs of a product / industrial designer: adjusting the environment to working on a smaller scale, rendering surfaces and materials and lighting set up for a "product shot".

All in all, this book is certainly worth the money and will be my first choice as a guide to improve my 3D skills.

Great Job, this book is good, but is very tiring. Because the subject is extensive.
Thank you!!

This book presents the current status of Large-Eddy Simulation (LES) and is invaluable for anyone working on the field.

The author presents all relevant subgrid scale models, the theoretical basis of the method, lessons from practical cases, etc

It is no accident that this is the 3rd revision in 4 years, collecting forewords from leading theoreticians along the way: Germano, Lesieur and Meneveau.

This is the second book entirely dedicated to lattice Boltzmann, which is a recent numerical method for solving the Navier-Stokes equations for fluid flow (generally) and related configurations/issues (specifically and most recently).

It can be regarded as the little brother of Succi's book The Lattice Boltzmann Equation for Fluid Dynamics and Beyond (Numerical Mathematics and Scientific Computation), as it is very similar, about half the length and came out 5 years later. It therefore represents a good complementary text to Succi's.

The authors follow roughly the same line of thought as Succi's, but differ in two major ways: 1) their theoretical discussions are not as pronounced but 2) they present a much larger number of applications and capabilities by lattice Boltzmann, on engineering issues.

This is an important and necessary book for any LB practitioner in search of ideas or anyone interested in finding out more about lattice Boltzmann.

This book gives a fairly detailed introduction into the 2D LB method. It includes helpful chunks of C/C++ that can be used to help write your own code. I would recommend this text to students that are having a hard time understanding the method based on the journal article literature available.

There is not a lot to learn for the expert in this field.

I purchased this text to assist me in completing my doctoral dissertation that is based on complexity theory. The authors simplify agent-based modeling to the point that anyone interested can quickly get indoctrinated into the arena and, at a minimum, be able to understand and converse the major topics. For those like me who wish to delve even further into the research of complexity, the text is a wonderful launching pad and source of reference.

'Managing Business Complexity' is a great start at bridging the significant academic work in complexity science over recent years to business applications. It provides an introduction to agent-based simulations and an overview of the characteristics and advantages of agents, and walks the reader through two illustrative examples. Such examples are especially helpful to readers with little or no previous experience using agent-based models.

Applications of complexity science to business are still in their infancy. As such, the discussion in the book leans towards the academic, and more pointedly towards programmers rather than business practitioners with scant scientific background. Future editions of this book might benefit from including further business applications, and including the impact to bottom line.

This book is highly recommended as an overview of this exciting subject and its applicability to business situations.

This is an absolutely marvelous text on the dynamics of flying the Flight Simulator. Nick Dargahi wrote this book for MSFS version 5.1. When he writes a sequel for later versions, I will buy it, even if 80 percent is repetition. The 20 percent will make it worth while.

The book covers the fundamentals of flying in an easy to read manner. Reading the book enabled me to unleash the power of my Microsoft Flight Simulator 95. The chapter on instrument navigation does a much better job than the fragmented online help. The final chapter of "Around the World in 80 hours" is guaranteed to give you more than 80 hours of fun. The Appendices contain a lot of pertinent data which makes this book a handy reference as well.

Overall, it's an excellent book on the practice of Monte Carlo and the c++ code in appendix are very instructive (Random Number Generators, Solid Monte Carlo Routines, etc.). It does have certain weaknesses though.

1) Sometimes the description are trivial in principle but written in great details. For example, on Pg 58 on the exact methods (so-called 'efficient way') of calculating averaged quantities from simulation.
2) Most of the content are heuristic. The discussion of the whole book is based on practice, although you do find something looks like a rigious proof (but no in fact). By rigious, I mean the proof should be based on Markov Chain and related properties of random process and statistical physics.

But as I said in the beginning, this is a invaluable book to anyone who wants to use Monte Carlo method in his/her domain. For myself, I am using this book as a reference to tackle functional optimization - Simulated Annealing, which is a very close sibling of Monte Carlo method.

This book covers a wide range of applications in Statistical Mechanics, with clear explanation, examples, tips, algorithms, and explicit programs at the end of the book. It is good for beginners and experienced alike, since it discusses "classical" and modern algorithms. It is a must for those who want to make actual numerical calculations in Statistical Physics.

I am a PhD student in Operations Management and this is one of the best books in Location Management. Very clear and very precise, I did not need a class to understand the material. Its definitely a must for any body who wants a background on Location Models

This is the 2nd best book after Ahuja et.al. book (Network Flows : Theory, Algorithms, and Applications, 1993). As I said, it's the 2nd best book -so don't be surprised if you found Ahuja's book more useful. However, Daskin did good job to compile both location and network analysis in a single text book. We can see many issues in these areas in this book. I'd love to see more integration both math model and algorithm in this book though. If you don't have Ahuja's book, you may wanna grasp one (it's out-of-stock) before getting this book. However, if you are new to do research in location and network, grasp Daskin's book. You won't be disappointed with this book!

It's a very straightforward manual that tests your analysis skills with very interesting questions... anyone can go through the lab exercises, but can you answer the questions??

The book is rather short. It assumes you have the accompanying network text for more details on various types of networks. There are 12 experiments, of varying complexity. Mostly for TCP/IP ethernet and ATM. You can try tweaking parameters and seeing how this impacts performance. Useful because nowadays, networking details can be pushed so deeply into low levels that it's hard to experiment and appreciate their intricacies.

There is one experiment for a token ring LAN. But who is still using this? IBM is phasing token ring out rapidly.

Parallel and Distributed Simulation Systems, by Richard Fujimoto, brings together all of the leading techniques for designing and operating parallel and distributed simulations. This is the first book to bring this material in a single source. Previously, simulation developers had to research a library to journal and conference articles to identify, master, and select techniques appropriate to their problem.

Fujimoto divides the material into three sections. The first introduces the reader to the real world problems that have given rise to the need for PADS techniques. He also includes an introduction to the field of discrete event simulation, laying the necessary groundwork for the reader to understand the rest of the book.

In the second section the book begins to describe many of the techniques that are used to accomplish parallel or distributed operations for discrete event simulations. These are presented very clearly and most readers will grasp them immediately. In this section, the reader gains an appreciation for the difficulty involved in creating parallel simulations that maintain the causality of events within the entire simulation. Distributing the application across multiple computers has the potential to greatly increase its execution speed, but must do so without jeopardizing the causal accuracy of the simulation. Topics covered include conservative synchronization, time warp, deadlock avoidance, lookahead, repeatability, global virtual time, scheduling, and performance. Fujimoto also includes a description of the Georgia Tech Time Warp system in which he and others have implemented many of these techniques.

Finally, the third section describes the application of PADS techniques to distributed virtual environments. Fujimoto focuses distributed military training systems and points toward the potential for applying these techniques in entertainment applications. This section is motivated by a description of the evolution of distributed military training using protocols like simulator networking (SIMNET), distributed interactive simulation (DIS), aggregate level simulation protocol (ALSP), and the more recent high level architecture (HLA). Fujimoto takes great care to describe how PADS techniques are used within software implementations of the HLA. Topics include distributed interactive simulation, dead reckoning, the high level architecture, network technologies, communication protocols, data distribution management, and message ordering.

The book is an essential tool for those creating parallel or distributed simulation applications or conducting research in the field. It provides and excellent level of detail and sufficient explanation to allow others to implement the techniques. It is available directly from Wiley-Interscience and from most of the Web-based bookstores.

This book is a very readable introduction to parallel and distributed computing. It presents concepts well, and offers enough examples to allow one to make sure they have a firm grasp on what is being presented. It is NOT a textbook. It is not full of code, or detailed descriptions of exactly how to implement a parallel/distributed system in a given situation. Those already expert in the field or those seeking low-level detail and code should look elsewhere. I recommend this book to everyone else.

I have not yet had any formal training on optimization so this book took a little getting used to. Once I got passed the basics, the text read well however. I imagine it would be an easy read if you've had any training in optimization. I now use it as a reference to look up similar problems I'm faced with; the author provides many general examples that are easily altered for more specific questions.

Practical Optimization Methods - M.Asghar Bhatti

This is my favorite optimisation book. I recommend it to anyone interested in the application of optimisation techniques, in particular for those in industry. This book has been a constant companion in my optimisation adventure and unlike other books; it has helped me firmly establish a solid foundation and understanding on the various optimisation techniques and the theories behind them. Believe me, I can even read those books which I have shelved in the past because they were complicated with too many cryptic mathematical statements. They don't scare me anymore.

Bhatti wisely used Mathematica as the teaching platform and the accompanying OptimizationToolbox software allows one to brush aside the cryptic mathematical statements. The reader can now concentrate on the concepts, relegating the mathematics manipulations to Mathematica and the functions of the OptimisationToolbox. What I like about this book is that it also shows how the Taylor Series, the Quadratic Form and convexity requirements are put into practice to create an iterative scheme to solve a system of non-linear equations. The OptimisationToolbox and the internal Mathematica functions seamlessly pace the reader through the mathematical preliminaries. By the end of Chapter 3, the reader should now be a good shape to go to the more serious stuffs.

Chapter 4 deals with the subject of optimality conditions starting first with the optimality conditions for unconstrained optimisation problems. These conditions, albeit slightly more involved in computation, are essentially the same as the optimality conditions for single variable functions of the high school days. The "slightly involved" computations are those of the Grad (1st Order and Necessary Condition) and the Hessian (2nd Order and Necessary). Mathematica graphics are put to great effect to help visualize the meaning of these conditions.

The additive property of constraints, which was dealt with in graphic detail, extends the earlier ideas behind the optimality conditions for an unconstrained optimisation to that for constrained optimisation problems.

The introduction to Chapter 5 gives an excellent overview of issues in solving unconstrained problems. Basically, all solution schemes covered in this chapter involve two steps. The first step is a simple iterative scheme, which requires a direction and a step length. The second step is a termination condition, taken as when the gradient of objective function, which should be zero at the optimal point, is sufficiently close to within a specified tolerance to zero.

The process of computing the step length in for a particular search direction is known as the line search. The line search methods (including Mathematica algorithms) covered include analytical line search, equal interval search, section search, the Golden Section search, the Quadratic Interpolation Method and the Approximate Line Search based on Armijo's rule.

As for the search direction, one obvious choice would be along the direction of greatest negative change - the Steepest Descent Method. The performance of this method can suffer badly as it zigzag search scheme slows down to a crawl as it approaches the optimal point. One improvement would be to retain some potion of the previous search direction, so the resultant search pattern is not successively perpendicular to each other but somewhere in between. This approach of adding some potion of the previous direction is known as the Conjugate Gradient Method. The two "some previous direction potion" schemes covered and included as Mathematica functions are the Fletcher-Reeves and the Polak-Ribiere schemes. Other numerical methods covered include the Modified Newton and the Quais-Newton Methods. One drawback of latter approach is the computation of the Hessian Matrix at each iteration step. The Quasi-Newton Methods do not require the computation of the Hessian Matrix. Instead they use some inverse Hessian update methods. Two such methods covered are the DFP (Davidon, Fletcher, and Powel) Update and the BFGS (Broyden, Fletcher, Goldfarb, and Shannon) Update. Don't be intimidated by all these jargons, Mathematica functions including graphic functions are provided to provide a step-by-step explanation and presentations of the various concepts are provided.

The section on Linear Programming is extensive, in comparison to other chapters. I was tempted to skim over this LP section because the technique is well known and there are many industry standard LP algorithms on the market so why spend too much time on it. However, my curiosity got the better of me and I must confess that the combination of the accompanying OptimisationToolbox and Mathematica Graphics makes the revision on Linear Programming entertaining and interesting. The section started with an overview of issues involved in solving an underdetermined system of linear equations; going over the Gauss-Jordan, LU decomposition and introduction of slack variables to convert the LP problem into its standard form. The simplex algorithm is introduced in three styles: Simplex Tableau, Basic Simplex and Revised Simplex. The first two simplex styles, as Mathematica functions by the way, are intended to show the sequence of steps of the simplex algorithm. For large problems, however, the above LP methods may take a long time and researchers have developed better search methods such as the interior point method. The interior point method, as its name implies, starts from an interior feasible point and takes appropriate steps alone descent directions towards the optimal point.

Chapters 8 & 9 adequately covered the subject of quadratic programming and constrained nonlinear problems. However, they concentrated only on local optimisation techniques. Inclusion of global optimisation methods such as Simulated Annealing (SA), Genetic Algorithms (GA), Discrete Gradient Methods (DGM), Hooke-Jeeves, Nelder and Mead, and Powell methods would have made the book a complete guide to practical optimisation.

My favorite Optimisation Book - Clear and Useful