Projects

Evolving Objects

EO is a template-based, ANSI-C++ evolutionary computation library which helps you to write your own stochastic optimization algorithms insanely fast. With the help of EO, you can easily design evolutionary algorithms that will find solutions to virtually all kind of hard optimization problems ... [More] , from continuous to combinatorial ones. Designing an algorithm with EO consists in choosing what components you want to use for your specific needs, just as building a structure with Lego blocks. [Less]

Divide and Evolve

A stochastic method for planning decomposition, called Divide-and-Evolve, that was introduced recently and which focuses on plan quality. The basic principle is to search the space of state decompositions of the planning problem at hand by means of artificial evolution: candidate solutions are ... [More] sequences of intermediate goals which define consecutive planning subproblems that are hopefully easier to solve than the global problem. The scope of Divide-and-Evolve is temporal planning as defined by PDDL2.1 (the widely adopted planning domain description language standard) where the problems are described using durative actions and where plan quality is the total makespan. [Less]

MOEA Framework

The MOEA Framework is an open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose optimization algorithms and metaheuristics. A number of algorithms are provided out-of-the-box, including NSGA-II, ε-MOEA, GDE3 and ... [More] MOEA/D. In addition, third-party tools like JMetal and PISA directly integrate with the MOEA Framework. The MOEA Framework targets an academic audience, providing the resources necessary to rapidly design, develop, execute and statistically test optimization algorithms. This includes over 40 test problems from the literature, and a suite of statistical tools for comparing and analyzing algorithm performance. [Less]