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|umontreal.iro.lecuyer.gof||This package contains tools for performing univariate goodness-of-fit (GOF) statistical tests.|
|umontreal.iro.lecuyer.hups||Monte Carlo and quasi-Monte Carlo|
|umontreal.iro.lecuyer.probdist||This package contains a set of Java classes providing methods to compute mass, density, distribution, complementary distribution, and inverse distribution functions for some discrete and continuous probability distributions.|
|umontreal.iro.lecuyer.probdistmulti||This package contains Java classes providing methods to compute mass, density, distribution and complementary distribution functions for some multi-dimensional discrete and continuous probability distributions.|
|umontreal.iro.lecuyer.randvar||This package provides a collection of classes for non-uniform random variate generation, primarily from standard distributions.|
|umontreal.iro.lecuyer.randvarmulti||This package provides a collection of classes for non-uniform random variate generation for multi-dimensional distributions.|
|umontreal.iro.lecuyer.rng||This package offers the basic facilities for generating uniform random numbers.|
|umontreal.iro.lecuyer.simevents||This package provides the simulation clock and tools to manage the future events list.|
|umontreal.iro.lecuyer.simevents.eventlist||This package provides different kinds of event list implementations.|
|umontreal.iro.lecuyer.simprocs||Process-oriented simulation is managed through this package.|
|umontreal.iro.lecuyer.stat||This package provides elementary tools for collecting statistics and computing confidence intervals.|
|umontreal.iro.lecuyer.util||This package contains utility classes used in the Java software developed in the simulation laboratory of the DIRO, at the Université de Montréal.|
SSJ is a Java library for stochastic simulation, developed in the Département d'Informatique et de Recherche Opérationnelle (DIRO), at the Université de Montréal. It provides facilities for generating uniform and nonuniform random variates, computing different measures related to probability distributions, performing goodness-of-fit tests, applying quasi-Monte Carlo methods, collecting statistics (elementary), and programming discrete-event simulations with both events and processes. Additional Java packages are also developed on top of SSJ for simulation applications in finance, call centers management, communication networks, etc.
Simulation models can be implemented in many ways. One can use general-purpose programming languages such as FORTRAN, C, C++, Java, or specialized simulation languages such as such as GPSS, SIMAN, and SIMSCRIPT. The general-purpose languages can be more familiar to the programmer, but usually do not have the necessary built-in tools to perform simulation. Implementing a model can become complex and tedious. Specialized simulation languages must be learned before models can be implemented, and they are not as widely available and supported as the most popular general-purpose languages.
Over the past few decades, commercial simulation tools with point-and-click graphical user interfaces such as Arena, Automod, Witness, and many others, have become by far the most widely used tools to develop simulation models. Among their main advantages, these tools do not require knowledge of a programming language, provide graphical animation, have automatic facilities to collect statistics and perform experiments, and can sometimes perform optimization to a certain extent. On the other hand, these specialized simulation tools, especially the point-and-click tools, are often too restrictive, because they are usually targeted at a limited class of models. With these tools, simulating a system whose logic is complicated or unconventional may become quite difficult. All the graphical and automatic devices also tend to slow down the simulation significantly. Fast execution times are important for example in a context of optimization, where thousands of variants of a base system may have to be simulated, or for on-line applications where a fast response time is required.
SSJ is an organized set of packages whose purpose is to facilitate simulation programming in the Java language. A first description was given in. Some of the tools can also be used for modeling (e.g., selecting and fitting distributions). As these lines are being written (August 2004), SSJ is still growing. Several new packages, classes, and methods will certainly be added in forthcoming years and others will be refined.
The facilities offered are grouped into different packages, each one having its own user's guide, in the form of a PDF file. There is also a set of commented examples of simulation programs in a separate PDF document. Programs are given for some of the examples used in the books of Law and Kelton and Glasserman, for instance. The best way to learn about SSJ, at the beginning, is probably to study these examples and refer to the user guides of the different packages when needed. The PDF files are the official documentation. There is also a simplified on-line documentation in HTML format, produced via javadoc.
The Colt library,
developed at the Centre Européen de Recherche
Nucléaire (CERN) in Geneva,
is a large library that provides a wide range of facilities for
high performance scientific and technical computing in Java.
SSJ uses the class
from Colt in a few of its classes, namely in packages
The reason is that this class provides a very efficient and convenient
implementation of an (automatically) extensible array of double,
together with several methods for computing statistics for the observations
stored in the array (see, e.g., Descriptive).
The Colt library is distributed with the SSJ package.
Here is the Colt License Agreement copied from the Colt web site:
Copyright (c) 1999 CERN - European Organization for Nuclear Research.
Permission to use, copy, modify, distribute and sell this software and its documentation for any purpose is hereby granted without fee, provided that the above copyright notice appear in all copies and that both that copyright notice and this permission notice appear in supporting documentation. CERN makes no representations about the suitability of this software for any purpose. It is provided "as is" without expressed or implied warranty.SSJ also provides an interface to the UNURAN library for nonuniform random number generation, in the
randvarpackage. UNURAN does not have to be installed to be used with SSJ, because it is linked statically with the appropriate SSJ native library. However, the UNURAN documentation will be required to take full advantage of the library.
The linear_algebra library is based on public domain LINPACK routines. They were translated from Fortran to Java by Steve Verrill at the USDA Forest Products Laboratory Madison, Wisconsin, USA. This software is also in the public domain and is included in the SSJ distribution as the Blas.jar archive, which must be in the CLASSPATH environment variable. It is used only in the probdist package to compute maximum likelihood estimators.
The optimization package of Steve Verrill includes Java translations of the MINPACK routines for nonlinear least squares problems as well as UNCMIN routines for unconstrained optimization. They were translated from Fortran to Java by Steve Verrill and are in the public domain. They are included in the SSJ distribution as the optimization.jar archive, which must be in the CLASSPATH environment variable. It is used only in the probdist package to compute maximum likelihood estimators.
SSJ was designed and implemented under the supervision of Pierre L'Ecuyer, with the contribution of the following persons
Mathieu Bague, Éric Buist, Yves Edel, Regina H. S. Hong, Alexander Keller, Pierre L'Ecuyer, Étienne Marcotte, Lakhdar Meliani, Abdelazziz Milib, François Panneton, Richard Simard, Pierre-Alexandre Tremblay, Jean Vaucher.
Its development has been supported by NSERC-Canada grant No. ODGP0110050, NATEQ-Québec grant No. 02ER3218, a Killam fellowship, and a Canada Research Chair to the author.
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