Search Results for "genetic algorithms"

jMetal is an object-oriented Java-based framework for solving multi-objective optimization problems with metaheuristics.

EASEA (EAsy Specification of Evolutionary Algorithms: pronounce "easy") is a high-level language dedicated to the specification of evolutionary algorithms. EASEA up to version 0.7 compiles .ez specification files into C++ or JAVA object files.

Critterding is a "Petri dish" universe in 3D that demonstrates evolving artificial life. Critters start out with completely random brains and bodies, but will automatically start evolving into something with much better survival skills.

quadGT is a software package for the joint genotyping of two parents, child’s normal genome and child’s tumor genome based on sequencing reads aligned to a reference genome.

an simple thread pool in linux, based on POSIX thread API. Management thread will retrieve needless idle thread to keep in low resource consumption.

Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and. Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments...

用c实现了常用的容器，如果rbtree,hashtable,list,vector,deque,heap,map,以及定时器，os api，应用开发框架。 实现了一个基于btree索引算法的文件数据库,提供了断电保护,以及事务提交与回滚等接口

Class winapi for windows XP.

CGL(C Generic Library) is a stl-like library written in pure C.It implements iterators, memory management,generic containers such as list,map, generic algorithms such as sort() and search(),and it can manipulate any types of data.

Can emulate old computer on text the code pogram ideal to create kernel for operating system The begin the project the can emulate CPU(8080)and z80.

A genetic algorithm framework to allow the evolution of synapse weights and topologies of artificial neural networks.

In silico evolution of biochemical networks using a genetic algorithm combined with a rule-based biochemical network model.