The aivika package
- 'ghc-options: -O2' is rarely needed. Check that it is giving a real benefit and not just imposing longer compile times on your users.
- Exposed modules use unallocated top-level names: Simulation
Aivika is a multi-method simulation library focused on discrete event simulation (DES) with partial support of system dynamics and agent-based modeling.
The library has the following features:
allows defining recursive stochastic differential equations of system dynamics (unordered as in maths via the recursive do-notation);
supports the event-driven paradigm of DES as a basic core for implementing other paradigms;
supports extensively the process-oriented paradigm of DES with an ability to resume, suspend and cancel the discontinuous processes;
allows working with the resources based on specified queue strategies (FCFS/FIFO, LCFS/LIFO, SIRO, static priorities and so on);
allows customizing the infinite and finite queues based on strategies too;
supports the resource preemption;
allows defining a queue network based on streams of data (transacts) and their processors;
allows simulating circuits with recursive links and delays;
supports the activity-oriented paradigm of DES;
supports basic constructs for the agent-based modeling such as agents, states, timeout and timer handlers;
allows creating combined discrete-continuous models as all parts of the library are well integrated and this is reflected directly in the type system;
the arrays of simulation variables are inherently supported;
supports the Monte-Carlo simulation;
the simulation model can depend on external parameters;
uses extensively signals for notification;
allows gathering statistics in time points;
hides technical details in high-level simulation computations (monads, streams and arrows).
Aivika itself is a light-weight engine with minimal dependencies. However, it has additional packages [1, 2] that offer the following features:
automating simulation experiments;
saving the results in CSV files;
plotting the deviation chart by rule 3-sigma, histogram, time series, XY chart;
collecting the summary of statistical data;
parallel execution of the Monte-Carlo simulation;
has an extensible architecture.
The charting package has two interchangeable back-ends [3, 4], where one of them uses Cairo and it is more preferable.
The PDF documentation and installation instructions are available on the Aivika Wiki website .
Moreover, the method was generalized  and applied to nested simulation  and parallel distributed simulation .
The libraries were tested on Linux, Windows and OS X.
A more full information about Aivika is available on the project website .
P.S. Aivika is actually a genuine female Mari name which is pronounced with stress on the last syllable.
|Versions||0.1, 0.2, 0.3, 0.4, 0.4.1, 0.4.2, 0.4.3, 0.5, 0.5.1, 0.5.4, 0.6, 0.6.1, 0.7, 1.0, 1.1, 1.2, 1.2.1, 1.3, 1.4, 2.0, 2.1, 3.0, 3.1, 4.0, 4.0.1, 4.0.3, 4.1, 4.1.1, 4.2, 4.3, 4.3.1, 4.3.2, 4.3.3, 4.3.4, 4.3.5, 4.5, 4.5, 4.6, 5.0.1|
|Dependencies||array (>=0.3.0.0), base (>=22.214.171.124 && <6), containers (>=0.4.0.0), mtl (>=2.1.1), random (>=126.96.36.199), vector (>=0.10.0.1) [details]|
|Copyright||(c) 2009-2016. David Sorokin <email@example.com>|
|Maintainer||David Sorokin <firstname.lastname@example.org>|
|Source repository||head: git clone https://github.com/dsorokin/aivika|
|Uploaded||Sun Jun 12 09:03:40 UTC 2016 by DavidSorokin|
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