This book has been used in courses at the Johns
Hopkins University, Morgan State University, and the University
of Maryland, among other institutions. At Johns Hopkins, the author
taught two graduate courses from this book, one in stochastic
optimization and one in simulation and Monte Carlo methods. These
were offered in the Department of Applied Mathematics and Statistics
as part of the fulltime graduate program and in the Applied and
Computational Mathematics and Electrical and Computer Engineering
Programs, which are divisions of the Johns Hopkins PartTime Engineering
Program (catering largely to people employed fulltime and pursuing
a master’s
degree by taking courses in the evening).
As a potential guide to faculty at other universities considering
similar courses, the syllabi for
courses in stochastic optimization and simulation and Monte Carlo
list the subjects in the abovementioned two courses. The prerequisites
for these courses are the same as the prerequisites for the book
(see excerpts from preface). The courses
cover a blend of theory and practical algorithm descriptions.
Each chapter and appendix contains examples and exercises for the
reader to use in practicing with the methods being described. A
partial set of solutions to the exercises is included at the back
of the book and at answers to
selected exercises. Faculty using this book as a text for a
course may request a more complete set of solutions by sending a
letter to the author on institutional letterhead. The request may
be sent to:
James C. Spall
The Johns Hopkins University
Applied Physics Laboratory
11100 Johns Hopkins Road
Laurel, Maryland 207236099
USA
For the most part, the two courses in the table cover
distinct material. However, because neither course is a prerequisite
for the other, there is a small amount of overlap. Appendices A
and B review material that most students should have encountered
prior to these classes, but since “encountered” and
“retained” are different things, it may be useful to
spend some time on these subjects. Appendices C, D, and E, on the
other hand, include material that may not be familiar to some students,
suggesting that these appendices might be covered more slowly. In
the simulation course, some material is drawn from supplementary
sources, as indicated in the table at syllabi
for courses in stochastic optimization and simulation and Monte
Carlo.
Aside from the graduate courses above, the material here has also
been used in short courses at conferences sponsored by the Institute
of Electrical and Electronics Engineers (IEEE), the American Statistical
Association, the U. S. Department of Defense, and the Society for
Computer Simulation.
PowerPoint Slides
Syllabi
for courses in stochastic optimization and simulation and Monte
Carlo
