- Referenced in 1074 articles
- Genocop, by Zbigniew Michalewicz, is a genetic algorithm-based program for constrained and unconstrained optimization...
- Referenced in 281 articles
- contrast to other evolutionary methods like genetic algorithms, scatter search is founded on the premise...
- Referenced in 250 articles
- results produced by ABC, Genetic Algorithm (GA), Particle Swarm Algorithm (PSO) and Particle Swarm Inspired...
- Referenced in 67 articles
- GAlib: A C++ Library of Genetic Algorithm Components. GAlib contains a set of C++ genetic ... library includes tools for using genetic algorithms to do optimization in any C++ program using ... overview of how to implement a genetic algorithm as well as examples illustrating customizations...
- Referenced in 104 articles
- Norwich, and Toulouse. The participants developed optimization algorithms based on branch-and-cut and constraint ... variety of local search methods, genetic algorithms, neural networks, and potential reduction. These algorithms were...
- Referenced in 91 articles
- multiobjective evolutionary algorithms - the Niched Pareto Genetic Algorithm (NPGA) and a nondominated sorting GA (NSGA...
- Referenced in 75 articles
- Genetic Algorithm Toolbox for MATLAB ® was developed at the Department of Automatic Control and Systems...
- Referenced in 51 articles
- combinatorial optimization, such as simulated annealing, genetic algorithms, iterated local search, tabu search, WalkSAT...
Genetic Algorithm and Direct Search Toolbox
- Referenced in 29 articles
- Genetic Algorithm and Direct Search Toolbox (GADS) extends the optimization capabilities in MATLAB ... with tools for using the genetic and direct search algorithms. You can use these algorithms ... unreliable or undefined derivatives. The Genetic Algorithm and Direct Search Toolbox complements other optimization methods...
- Referenced in 35 articles
- robust and reactive tabu search, hybrid genetic algorithm, and a simulated annealing method. Experimental results ... that HAS-QAP and the hybrid genetic algorithm perform best on real world, irregular...
- Referenced in 22 articles
- Genetic Algorithms. An R package for optimization using genetic algorithms. The package provides a flexible ... purpose set of tools for implementing genetic algorithms search in both the continuous and discrete ... depending on the problem at hand. Several genetic operators are available and can be combined...
- Referenced in 18 articles
- MOTGA: a multiobjective Tchebycheff based genetic algorithm for the multidimensional knapsack problem. A new multiobjective ... genetic algorithm based on the Chebyshev scalarizing function, which aims to generate a good approximation ... called MOTGA (multiple objective Chebyshev based genetic algorithm) has been designed to the multiobjective multidimensional...
- Referenced in 18 articles
- grouping genetic algorithm for the cell formation problem. In manufacturing, the machine-part cell formation ... paper presents and tests a grouping genetic algorithm (GGA) for solving the MPCF problem ... this study, CF-GGA, a grouping genetic algorithm for the cell formation problem, performs very...
- Referenced in 26 articles
- GENetic Optimization Using Derivatives. A genetic algorithm plus derivative optimizer. Genoud is a function that...
- Referenced in 16 articles
- general-purpose, data-structure-neutral parallel GENETIC ALGORITHM library. It is intended to provide most ... capabilities desired in a genetic algorithm library, in an integrated, seamless, and portable manner. Features...
- Referenced in 20 articles
- GEATbx - The Genetic and Evolutionary Algorithm Toolbox for Matlab. The Genetic and Evolutionary Algorithm Toolbox ... your method of choice! Powerful genetic and evolutionary algorithms find solutions to your problems...
- Referenced in 13 articles
- BIANCA: a genetic algorithm to solve hard combinatorial optimisation problems in engineering The genetic algorithm ... composite laminates is a multi-population genetic algorithm capable to deal with unconstrained and constrained ... information is extensively exploited during genetic operations. Moreover, we developed proper and original strategies...
- Referenced in 15 articles
- deterministic computer simulators. They used a genetic algorithm based approach that is robust but computationally ... robust and typically faster than the genetic algorithm based approach. We present two examples with...
- Referenced in 11 articles
- Stellar structure modeling using a parallel genetic algorithm for objective global optimization. Genetic algorithms ... optimization subroutine PIKAIA, which utilizes a genetic algorithm to provide an objective determination ... parameter-space made possible by genetic-algorithm-based numerical optimization led us to a number...
- Referenced in 19 articles
- using either manual selection or a genetic algorithm. VICONOPT models are validated with ABAQUS finite...