ParadisEO-MO: Single solution based metaheuristics
Paradiseo-MO is a general-purpose software framework dedicated to the design and the implementation of single solution based metaheuristics and tools for fitness landscape analysis. It is based on a conceptual model that tends to unify a substantial number of state-of-the-art methodologies proposed so far. All those methods are here considered as simple variants of the same structure: a fine-grained decomposition of the general schema of local searches.
ParadisEO-MO is a white-box, object-oriented, C++, easy-to-use framework, portable across both Unix-like (Linux, MacOS) and Windows systems. It is governed by the CeCILL license. The framework embeds some features and techniques for "fitness landscape analysis" and aims to provide a set of classes allowing to ease and speed up the development of computationally efficient programs. The rich set of ParadisEO-MO modular classes are combined to develop single solution based metaheuristics.
The related source code is maintained and regularly updated by the developers. Moreover, the framework perpetually evolves according to the needs and facilitates the development of new algorithms, either sequential or parallel, with a minimum effort. The ParadisEO-MO module is based on a clear conceptual separation of the solution methods from the problems they are intended to solve. This separation confers a maximum code and design reuse to the user. For instance, to solve your own real-coded problem by means of local searches, you have just to define your evaluation function and your neighborhood structure.
This makes from ParadisEO-MO a valuable tool for the scientific research community, the educational world and industrial organizations. The module tends to be used by both researchers and practitioners, non-specialists and experts, and has proven its validity and high flexibility by enabling the resolution of many academic and real-world problems.
Summary of Features
- Portability: Windows, Unix and MacOS, optionally on parallel and distributed architectures
- Easy-to-use state-of-the-art local searches (based on the aforementioned components)
- Hill-climbing, Random Walk, Metropolis Hasting, Simulated annealing, Tabu search, Iterated local search...
- Solution representation for problems of continuous and combinatorial nature
- binary-strings, integer, permutation, user-defined representation
- Tools to perform the fitness landscapes analysis
- Density Of States
- Fitness Distance Correlation
- Autocorrelation length and function
- Sampling the local optima by adaptive walks
- Neutral degree distribution
- Evolvability of neutral networks by neutral walks
- Fitness Cloud
- Problem implementations to be plugged onto ParadisEO-MO are available for download as contributions