The Kotlin Simulation Library (KSL) is a Kotlin library for performing Monte Carlo and Discrete-Event Dynamic System computer simulations.
The KSL has the following functionality:
- Discrete event calendar and executive
- Random number stream control
- Discrete and continuous random variate generation
- Bernoulli, Beta, ChiSquared, Binomial, Constant, DUniform, Exponential, Gamma, GeneralizedBeta, Geometric, JohnsonB, Laplace, LogLogistic, Lognormal, NegativeBinomial, Normal, PearsonType5, PearsonType6, Poisson, ShiftedGeometric, Triangular, Uniform, Weibull, DEmpirical, Empirical, AR1Normal
- Statistical summary collection including histograms and box plots
- Probability distribution modeling
- Monte Carlo simulation
- Event view modeling
- Process view modeling
- non-stationary arrivals
- entity modeling, movement
- resources, mobile resources
- conveyors
- Simulation data collection to Excel, CSV, databases, and data frames
- Utility extensions for working with arrays and files
The KSL is licensed under the GPL 3.0
Why the GPL and not the LGPL? The KSL has functionality that could be used to form propriety simulation software. Using the GPL rather than the LGPL prevents this from happening. Developers and companies are free to use the KSL. Nothing prevents its use in performing (in-house) simulation analysis within industry. In fact, this is encouraged. However, developers or companies that want to build and extend the KSL (especially for commercial or proprietary reasons), are not permitted under the GPL, unless they want to release the functionality under the GPL. Developers and companies are encouraged to add functionality to the KSL and release the functionality so that everyone can benefit. Developers who want to extend the KSL for proprietary or commercial purposes can contact the KSL development team for other possible licensing arrangements.
If you are using IntelliJ, you can use its clone repository functionality to set up a working version. Or, simply download the repository and use IntelliJ to open up the repository. IntelliJ will recognize the KSL project as a gradle build and configure an appropriate project.
This is a Gradle based project.
https://rossetti.github.io/KSLBook/
The book explains how to use the KSL. For example, in Chapter 6 of the text, you will see fully worked out examples of how to implement the process view of simulation. For example, to simulate a simple M/M/c queue, code such as this can be easily developed using the KSL. This code models the usage of a resource via suspending functions, seize(), delay(), and release(). In addition, it collects statistics on the processing of the entities.
private inner class Customer : Entity() {
val pharmacyProcess: KSLProcess = process() {
wip.increment()
timeStamp = time
val a = seize(worker)
delay(serviceTime)
release(a)
timeInSystem.value = time - timeStamp
wip.decrement()
numCustomers.increment()
}
}
There is also a video series that provides an overview of getting started with the KSL and some of the associated material from the textbook.
If you are looking for the KSL API documentation you can find it here:
https://rossetti.github.io/KSLDocs/
The repository for the documentation is here:
https://github.com/rossetti/KSLDocs
Please be aware that the book and documentation may lag the releases due to lack of developer time.
The KSL is organized as a multi-project gradle build.
KSLCore - the main simulation functionality.
Additional projects are available for illustrating and other work related to the KSL.
KSExamples - a project that has example code that illustrates the KSL and contains the examples shown in the textbook.
KSLProjectTemplate - a pre-configured project using gradle that is set up to use the KSL
KSLTesting - a separate project that does some basic testing related to the KSL
group = "io.github.rossetti" name = "KSLCore" version = "R1.1.6"
Latest Release R1.1.6
- Added blockUntilAllCompleted() suspending function to permit suspension until a set of processes completes.
- Added home base concept for MovableResource
- Completed MSER work for initialization bias deletion point detection
- Completed LogisticFunction scaling implementation for MODA and use in PDFModeler
- Fixed after replication termination issue for suspended processes using the waitFor() suspending function
- Added examples for entity movement
Release: R1.1.5
- Added blockUntilCompleted() suspending function to permit suspension until another process completes
- Simplified basic suspend() function
Release: R1.1.4
- updated how processes are started, removed automatic use of process sequence
- fixed random number stream assignment issue
- added piecewise constant continuous empirical random variable and distribution
- minor enhancements to pdf scoring and fitting
- fixed bootstrap standard error estimate
- refactoring to enable future removal of Apache POI dependency
Release: R1.1.3
- Added ability of IndicatorResponse to observe ResponseCIfc
- Fixed stupid bug in EventGenerator introduced by typo in release 1.1.2.
Release: R1.1.2
- Added SAM functional interfaces to station package
- Don't use R1.1.2 due to stupid bug in EventGenerator, now fixed in R1.1.3
Release: R1.1.1
- Added ksl.modeling.station package
- facilitate modeling of simple queueing systems
- added maps that can have randomly selected elements
- improved RList, DUniformList
- added BernoulliPicker
Release: R1.1.0
- Updates to ksl.utilities.distributions.fitting package
- default scoring models changed to Bayesian Information Criterion, Anderson-Darling, Cramer Von-Mises, Q-Q Correlation
- Bug fixes for scaling algorithm
- Ranking criteria for recommending the distribution
- Bootstrap family recommendation
- Enhancements to database utilities
- Support for DuckDb database
- Creation of simple databases based on data classes
- Improved creation of SQLite, Derby and DuckDb databases
- Improved database connection usage
- Enhancements to MODA (multi-objective decision analysis) package.
- Improved defintion of metrics and support for database of results.
- New MODAAnalyzer class to analyze simulation output based on MODA principles.
- Enhancements to MultipleComparisonAnalyzer
- Save analysis to database
- Statistics
- Data classes for saving observations, statistics, histogram, frequencies to database
- Bug fix for Beta pdf calculation
- StringFrequency tabulation
- ErrorMatrix tabulation of confusion matrix results
- Removed dependency on OpenCSV
- Upgraded to kotlin 1.9.20
Release: R1.0.9
- Bug fixes and improvements in ksl.utilities.distributions.fitting package
- fixed Weibull estimation edge cases
- added additional output to html distribution fitting results
- Added capability in ksl.controls.experiments package to run many scenarios and perform designed experiments
- Improved support for data frame processing
- Updates to documentation and examples to be consistent with textbook
Release: R1.0.8
- Addressed new issue with search interval for MLE computation of gamma shape parameter
Release: R1.0.7
- Fixed natural logarithm compute issue in Anderson-Darling test statistic
- Fixed interval search issue for Gamma MLE parameter estimation
- Added 1-D discrete Metropolis-Hasting Markov Chain, improved properties of DMarkovChain
- Allow PMF to CDF with 0 probability on mass points
- Updates to documentation, examples
Release: R1.0.6
- Fixed AcceptanceRejectRV to correctly use majorizing function
- added Logistic random variable and distribution
- updated RVParameters and RVType for more flexibility
- added Laplace distribution
- improved KSLArrays.isAllEqual() and isAllDifferent() to account for double precision
- improved histogram break point creation
- simplified interface for TruncatedRV
Release: R1.0.4
- Fixed axis label issue in ScatterPlot
- Added examples for bootstrapping, VRT, and MCMC
- New classes for multi-variate copulas, minor revisions in mcmc package
- New regression functionality
- New case based bootstrap sampling functionality
- Improved control variate implementation
Release: R1.0.3
- fixed issue with PMFModeler that caused bin probabilities to be incorrectly updated
- added ability to save plots to PDFModeler
Release: R1.0.2
- added support for plotting output from simulation (ksl.utilities.io.plotting)
- added distribution fitting and testing capabilities (ksl.utilities.distributions.fitting)
- added conveyors for process modeling (ksl.modeling.entity.Conveyor)
- revised database structure (ksl.utilities.io.dbutil.KSLDatabase)
- added multi-objective decision analysis functionality (ksl.utilities.moda)
- dataframe I/O (ksl.utilities.io.DataFrameUtil)
- updated examples in KSLExamples project
- updated KSLProjectTemplate to use new release