CD-ROM with extensive C++ source code that
supports physical
simulation; has many illustrative applications
for Windows,
Linux, and OS X; and is compatible with many
game
engines?including the Wild Magic engine,
for which the complete
source code is included.
Contains sample applications for shader programs
(OpenGL and
DirectX), including deformation by vertex
displacement, skin and
bones for smooth object animation, rippling
ocean waves with
realistic lighting, refraction effects, Fresnel
reflectance, and
iridescence.
Covers special topics not found elsewhere,
such as linear
complementarity problems and Lagrangian dynamics.
Includes exercises for instructional use
and a review of
essential mathematics.
Game Physics is an introduction to the ideas
and techniques
needed to create physically realistic 3D
graphic environments. As
a companion volume to Dave Eberly’s industry
standard 3D Game
Engine Design, Game Physics shares a similar
practical approach
and format. Dave includes simulations to
introduce the key
problems involved and then gradually reveals
the mathematical and
physical concepts needed to solve them. He
then describes all the
algorithmic foundations and uses code examples
and working source
code to show how they are implemented, culminating
in a large
collection of physical simulations. This
book tackles the
complex, challenging issues that other books
avoid, including
Lagrangian dynamics, rigid body dynamics,
impulse methods,
resting contact, linear complementarity problems,
deformable
bodies, mass-spring systems, friction, numerical
solution of
differential equations, numerical stability
and its relationship
to physical stability, and Verlet integration
methods. Dave even
describes when real physics isn’t necessary?and
hacked physics
will do.
Features
CD-ROM with extensive C++ source code that
supports physical
simulation; has many illustrative applications
for Windows,
Linux, and OS X; and is compatible with many
game
engines?including the Wild Magic engine,
for which the complete
source code is included.
Contains sample applications for shader programs
(OpenGL and
DirectX), including deformation by vertex
displacement, skin and
bones for smooth object animation, rippling
ocean waves with
realistic lighting, refraction effects, Fresnel
reflectance, and
iridescence.
Includes exercises for instructional use
and a review of
essential mathematics.
ISBN: 1-55860-740-4 Book/Hardback
Measurements: 187 X 235 mm
Pages: 800
Publication Date: 14 January 2004
Handbooks in Operations Research and Management
Science, 10
Description
This Handbook Volume brings together leading
experts in the most
important sub-fields of stochastic programming
to present a
rigorous overview of basic models, methods
and applications of
stochastic programming. The work is intended
for researchers,
students, engineers and economists, who encounter
in their work
optimization problems involving uncertainty.
The area of stochastic programming was created
in the middle of
the last century, following fundamental achievements
in linear
and nonlinear programming. However, because
of the inherent
difficulty of stochastic optimisation problems,
it took a long
time until efficient solution methods were
developed. In the last
two decades a dramatic change in our abilities
to solve
stochastic programming problems took place.
It is partially due
to the progress in large scale linear and
nonlinear programming,
in nonsmooth optimization and integer programming,
but mainly it
follows the development of techniques exploiting
specific
properties of stochastic programming problems.
Computational
advances are also due to modern parallel
processing technology.
Nowadays we can solve stochastic optimization
problems involving
tens of millions of variables and constraints.
Contents
Preface.
Chapters.
Stochastic Programming Models (A. Ruszczynski,
A. Shapiro).
Optimality and Duality in Stochastic Programming
(A. Ruszczynski,
A. Shapiro).
Decomposition Methods (A. Ruszczynski).
Stochastic Integer Programming (F.V. Louveaux,
R. Schultz).
Probabilistic Programming (A. Prekopa).
Monte Carlo Sampling Methods (A. Shapiro).
Stochastic Optimization and Statistical Inference
(G. Ch. Pflug).
Stability of Stochastic Programming Problems
(W. Romisch).
Stochastic Programming in Transportation
and Logistics (W.B.
Powell, H. Topaloglu).
Stochastic Programming Models in Energy (S.W.
Wallace, S.-E.
Fleten).
Year 2003
Hardbound
ISBN: 0-444-50854-6
700 pages
672 pp.; 81 line illus; 6-1/8 x 9-1/4; 0-19-515296-4
Change is constant in everyday life. Infants
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