Originally, the Ant Algorithms are used to solve discrete and combinatorial optimization problems. Various extensions of Ant Colony Optimization (ACO) are proposed to deal with optimization problems, defined in continuous domains. One of the most useful algorithms of this type, is ACOR, the Ant Colony Optimization for Continuous Domains, proposed by Socha and Dorigo, in 2008 (here).
ACOR is an Estimation of Distribution Algorithm (EDA); because it is looking for a probabilistic model, which generates promising solutions of an optimization problem with higher likelihood and at every iteration of the algorithm, the model is updated to generate more promising solutions.
In this post, we are going to share with you, the open-source implementation of Ant Colony Optimization for Continuous Domains (ACOR) in MATLAB. The algorithm is implemented in a structured manner and if you are familiar with MATLAB programming language, you will find it easy, to use the codes in your research projects.
If you are looking for discrete version of Ant Colony Optimization (ACO), you can find the MATLAB implementation of ACO, in the following link: Implementation of ACO in MATLAB.
The download link of this project follows.
Implementation of ACO for Continuous Domains (ACOR) in MATLABDownload
Citing This Work
If you wish, you can cite this content as follows.
Cite as:Mostapha Kalami Heris, ACO for Continuous Domains in MATLAB (URL: https://yarpiz.com/67/ypea104-acor), Yarpiz, 2015.