GenLib Framework for genetic algorithm optimization
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GenLib Tags

Library Genetic algorithm solver Genetic algorithm Algorithm optimization algorithm bilateral algorithm Prim Algorithm genetic image genetic algorithm framework create genetic algorithm analyze algorithm genetic data CSCAN algorithm SSTF Algorithm genetic change genetic algorithm library raytracing algorithm Genetic System create algorithm make genetic algorithm Dijkstra Algorithm genetic sequence genetic information BWT algorithm Genetic algorithm library Axiom algorithm algorithm visualization view algorithm FPM algorithm learn algorithm NSTL Algorithm UPGMA algorithm analyze genetic algorithm implement algorithm GNFS algorithm Genetic code simulation Genetic code BIDI algorithm algorithm colection algorithm optimization implement genetic algorithm eucledian algorithm implement Midpoint2D-Algorithm genetic map creator create genetic map doomsday algorithm Euclide algorithm DLX algorithm Wunsch algorithm genetic algorithm component genetic programming downstream genetic program genetic programming framework build algorithm Genetic transduction pathway genetic distances calculator genetic map genetic algorithm optimization Pintail algorithm Levenberg-Marquardt algorithm genetic variation analysis analyze genetic variation parsimony ratchet algorithm two-allele genetic simulation codominant genetic markers Genetic Distance simulate genetic map genetic map simulation genetic model genetic study genetic drift identify genetic barriers simulate genetic diversity molecular genetic diversity molecular genetic Vigenere Algorithm insertionsort algorithm selectionsort algorithm analyze genetic association genetic differentiation genetic optimizing computer algorithm Genetic Algorithms optimization problem/algorithm

GenLib Description

GenLib stands for Genetic algorithm Library, whose main purpose is to provide the basis for applications which use genetic algorithms for solving optimization problems. Original idea was to come up with the design, which would support variety of types of objectives as well as single and multiple optimization within the same framework. Another goal would be to allow easy (once one managed to understand the library design) assembling and testing of variety of algorithms by combining genetic operators. GenLib is a handy algorithm library for solving optimization problems.

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