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]

METSlib Optimization Framework

METSlib is an OO (Object Oriented) metaheuristics framework in C++. Model and algorithms are modular: all the implemented search algorithms can be applied to the same model and personalized algorithms can be applied to very different models. METSlib implements the basics of some metaheuristics ... [More] algorithm: Random Restart Local Search, Variable Neighborhood Search, Iterated Local Search, Simulated Annealing (with linear, exponential and custom cooling schedule), and last but not least Tabu Search. [Less]

Wintermute

Wintermute is the attempt of Danté Ashton and a group of others to implement the world's first personal edition of an intelligent framework of applications and libraries, and in the future, an intelligent operating system. This is the brainchild of the [http://www.thesii.org/ SII]. Wintermute ... [More] bolsters the capabilities of using neural networking to learn about its host, a pseudo-langauge engine that permits translations and grammar rulesets of any language to be incorporated into the system, and database downloads of different sets of data to permit the combination of the world's first personal virtual self-thinking assistant. It can be used to perform simple tasks like dictation to a favorite word editor to more complex tasks, like sorting documents depending .. [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]

coderszone

A place where to put all interesting Java stuff! Currently developing: Genetic Algorithm - luisfurnas RSA Semiprimes factorization - luisfurnas GUI Utilities - luisfurnas Math Goodies - luisfurnas

vl-heurstics-ss09

no description

kodkod-heuristics

no description yet

pyheuristics

General framework and many particular heuristics written in python. The collection includes genetic algorithms, evolutionary algorithm, artificial ant colony algorithm, genetic programming, swarm algorithms, artificial immune systems, harmony search, hyperheuristics and many others. Heuristics can be run on single machine or in parallel mode.

operationsresearch

El proyecto consiste en el diseño de algoritmos heurísticos para solucionar el problema de Programación de Proyectos con Recursos Limitados y Múltiples Objetivos. Está dividido en varias etapas: Estudio de los objetivos de interés a optimizar, Cálculo de cotas inferiores y superiores para ... [More] dichos objetivos, Diseño de algoritmos de solución, Validación y Comparación de Resultados y Evaluación de posibles aplicaciones reales. En esta etapa de proyecto (Cálculo de cotas inferiores y superiores) nos enfocamos inicialmente en calcular una buena cota inferior para el objetivo de minimización del Makespan (duración del proyecto). Para el cálculo de dicha cota inferior se parte de las definiciones de otras cotas como la cota de la Ruta Crítica (LB0), la cota de Stinson (LBS) y la cota basada en Recursos (LBR). Se trata de reducir el problema eliminando actividades hasta tener sólo dos cadenas de actividades y solucionar el problema resultante por medio de métodos de Branch and Bound. [Less]

aco4vrp

Mas tarde con mucho gusto....