aivika: A multi-paradigm simulation library

[ bsd3, library, simulation ] [ Propose Tags ]

Aivika is a multi-paradigm simulation library with a strong emphasis on Discrete Event Simulation (DES) and System Dynamics (SD).

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;

  • allows defining a queue network based on infinite streams of data and their processors, where we can define a complex enough behaviour just in a few lines of code;

  • allows simulating circuits with recursive links and delays;

  • supports the activity-oriented paradigm of DES;

  • supports the basic constructs for the agent-based modeling;

  • 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 and arrows).

Aivika itself is a light-weight engine with minimal dependencies. However, it has additional packages Aivika Experiment [1] and Aivika Experiment Chart [2] that offer the following features:

  • automating the 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;

  • have an extensible architecture.

All three libraries were tested on Linux, Windows and OS X.

The PDF documentation is available on the Aivika Wiki [3] website.




P.S. Aivika is actually a genuine female Mari name which is pronounced with stress on the last syllable.


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Versions [RSS] 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, 4.6, 5.0.1, 5.1, 5.2, 5.3, 5.3.1, 5.4, 5.5, 5.6, 5.7, 5.8, 5.9, 5.9.1
Dependencies array (>=, base (>= && <6), containers (>=, mtl (>=2.1.1), random (>=, vector (>= [details]
License BSD-3-Clause
Copyright (c) 2009-2014. David Sorokin <>
Author David Sorokin
Maintainer David Sorokin <>
Category Simulation
Home page
Source repo head: git clone
Uploaded by DavidSorokin at 2014-10-30T18:42:31Z
Distributions NixOS:5.9.1
Downloads 38682 total (81 in the last 30 days)
Rating 2.0 (votes: 1) [estimated by Bayesian average]
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