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Public Software
- Software package: ACOTSP.V1.03.tgz
Author: Thomas Stützle.
Short description: This software package provides an implementation of various Ant Colony Optimization (ACO) algorithms applied to the symmetric Traveling Salesman Problem (TSP). The ACO algorithms implemented are Ant System, Elitist Ant System, MAX-MIN Ant System, Rank-based version of Ant System, Best-Worst Ant System, and Ant Colony System.
Aim of the software: Provide an implementation of ACO algorithms for the symmetric TSP under one common framework. The implementation is reasonably high performing.
License: GPL
Programming language: Developed in ANSI C under Linux (no guarantees that it works nicely under Windows; however, some limited tests showed that the code also works fine under Windows and Mac OS X).
Comment: This is Version 1.03 of ACOTSP; it is in large part identical to the software used to produce the results in the book Ant Colony Optimization by Marco Dorigo and Thomas Stüzle, MIT Press, Cambridge, MA, USA, 2004. It has been slightly re-structured, adapted to make the code more readable, some more comments were added, and a new command line parser was generated with Opag, Version 0.6.4.
The ACOTSP software has been ported to Java by Adrian Wilke and is available here.
- Software package: antnet-1.1-src.tar
Author: Muddassar Farooq.
Short description: An implementation of AntNet in Omnet++.
License: GPL
Programming language: Developed in Omnet++.
Comment: The model implements the AntNet routing algorithm proposed in: G. Di Caro and M. Dorigo. AntNet: Distributed Stigmergetic Control for Communications Networks. Journal of Artificial Intelligence Research, 9:317-365, 1998. It requires OMNeT++ 2.3 or later.
- Software package: hc-mmas-ubqp.tar.gz
Author: Christian Blum.
Short description: A MAX-MIN Ant System (MMAS) implemented in the Hyper-Cube Framework for the application to Unconstrained Binary Quadratic Programming (UBQP).
Aim of the software: Educational (not high-performance); it shows how to implement a MMAS in the Hyper-Cube Framework.
License: GPL
Programming language: Developed in C++ under Linux (no guarantees that it works under Windows).
Comment: A description of the implemented algorithm can be found in the paper The Hyper-Cube Framework for Ant Colony Optimization, which is published in IEEE Transactions on Systems, Man, and Cybernetics -- Part B.
- Software package: GUIAnt-Miner.zip
Authors: Fernando Meyer and Rafael Stubs Parpinelli.
Short description: GUI Ant-Miner is a tool for extracting classification rules from data.
It is an updated version of a data mining algorithm called Ant-Miner (Ant Colony-based Data Miner), which was proposed in 2002 by Parpinelli, Lopes
and Freitas. GUI Ant-Miner differs from the original algorithm as follows: It has a friendly graphical user interface, makes possible the use of ant
populations within the Ant Colony Optimization (ACO) concept, data input file is standardized with the well-known Weka system, and runs on
virtually any operating system since it is written in Java.
Aim of the software: This software is freely available for research and teaching (not a high-performance code).
License: GPL
Programming language: Java.
Comment: For further information concerning Ant-Miner and principles involved with it, please refer to: Parpinelli, R.S., Lopes, H.S., Freitas, A.A.
"Data mining with an ant colony optimization algorithm". IEEE Transactions on Evolutionary Computation, special issue on Ant Colony Algorithms, v. 6, n. 4, p. 321-332, August, 2002.
- Software package: Myra
Author: Fernando Esteban Barril Otero.
Short description: Myra is a cross-platform Ant Colony Optimization framework written in Java.
It provides a specialised data mining layer to support the application of ACO
to classification problems, including the implementation of Ant-Miner and
cAnt-Miner algorithms. The latter is an extension of Ant-Miner, which is able
to cope with continuous attributes directly - i.e. cAnt-Miner does not requires
a discretization method in a preprocessing step.
Aim of the software: Provides an implementation of both Ant-Miner and cAnt-Miner classification algorithms. The implementation is reasonably high performing, in terms of execution time and memory consumption.
License: LGPL
Programming language: Java.
Comment: For further information, please refer to "cAnt-Miner: An Ant Colony Classification Algorithm to Cope with Continuous Attributes". In Proceedings of the 6th International Conference on Ant Colony Optimization and Swarm Intelligence (ANTS 2008), Lecture Notes in Computer Science 5217, pp. 48-59. Springer-Verlag, 2008.
- Software package: AntSolver.tgz
Author: Christine Solnon.
Short description: AntSolver is a program for solving constraint satisfaction problems with ACO.
License: CeCILL-B FREE SOFTWARE LICENSE
Programming language: Developed in C.
Comment: Further information can be found here.
- Software package: AntClique.tgz
Author: Christine Solnon.
Short description: AntClique is a program for solving maximum clique problems.
License: CeCILL-B FREE SOFTWARE LICENSE
Programming language: Developed in C.
Comment: Further information can be found here.
- Software package: AntCar.tgz
Author: Christine Solnon.
Short description: AntCar is a program for solving the car sequencing problem.
License: CeCILL-B FREE SOFTWARE LICENSE
Programming language: Developed in C.
Comment: Further information can be found here.
- Software package: AntMiner+ v1.0.rar
Authors: Bart Minnaert and David Martens.
Short description: AntMiner+ is a classification technique which is based on the principles of Ant Colony Optimization.
Aim of the software: The goal is to infer comprehensible rule-based classification models from a data set.
License: Copyright (c) 2011, Bart Minnaert, All rights reserved.
Programming language: Matlab.
Website: http://www.antminerplus.com/
Comment: The AntMiner+ implementation is based on:
- D. Martens, M. De Backer, R. Haesen, J. Vanthienen, M. Snoeck and B. Baesens, "Classification with Ant Colony Optimization", in IEEE Transactions on Evolutionary Computation Vol. 11, Nb. 5, pp. 651-665, 2007.
- B. Minnaert, D. Martens, M. De Backer and B. Baesens, "To Tune or not to Tune: Rule Evaluation for Metaheuristic-based Sequential Covering Algorithms", in FEB Working paper 2012/769, University Ghent, January 2012.
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