MHTB offers a number of libraries of metaheuristic algorithms implemented in C/C++ and Java to be used from MATLAB. It is aimed at a large number of potential users of the metaheuristic algorithms that, in spite of knowing the MATLAB language quite well, desist from applying these libraries because of their lack of knowledge in the programming languages they are implemented in.
Although there are some other MATLAB toolboxes that offer metaheuristic algorithms, our software has the following advantages compared to them:
- The offered libraries are implemented in C/C++ and Java. They are, in general, more efficient than the ones implemented in MATLAB. Furthermore, the amount of available software in those languages widely exceeds the one existing in MATLAB.
- It allows the parallel execution of the algorithms. Some of the existing toolboxes offer distributed versions of their algorithms, but they can not be physically distributed.
- It is not limited to a particular metaheuristic, but it covers a broad range in the field of metaheuristics.
The main features of our toolbox are the following:
- You can solve optimization problems defined in the MATLAB language using metaheuristic algorithms.
- You may also implement your own operators in the MATLAB language and use them from the libraries, if they allow it.
- If you have developed a metaheuristic algorithms library and you want to integrate it into our toolbox, we offer you a guide with the steps you must follow to do it.
- Simulated Annealing: Available in MALLBA
- Genetic Algorithm: Available in ssGA, jEA, MALLBA
- Evolutionary Strategy: Available in jEA, MALLBA
- CHC Algorithm: Available in MALLBA