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evolutionary-optimization-laboratory
rmoo:Multi-Objective Optimization in R
The 'rmoo' package is a framework for multi- and many-objective optimization, which allows researchers and users versatility in parameter configuration, as well as tools for analysis, replication and visualization of results. The 'rmoo' package was built as a fork of the 'GA' package by Luca Scrucca(2017) <DOI:10.32614/RJ-2017-008> and implementing the Non-Dominated Sorting Genetic Algorithms proposed by K. Deb's.
Maintained by Francisco Benitez. Last updated 5 months ago.
metaheuristicsmultiobjectivemultiobjective-optimizationnsgansga2nsga3optimizationpareto-front
30 stars 5.01 score 23 scriptsantonio-pgarcia
evoper:Evolutionary Parameter Estimation for 'Repast Simphony' Models
The EvoPER, Evolutionary Parameter Estimation for Individual-based Models is an extensible package providing optimization driven parameter estimation methods using metaheuristics and evolutionary computation techniques (Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization for continuous domains, Tabu Search, Evolutionary Strategies, ...) which could be more efficient and require, in some cases, fewer model evaluations than alternatives relying on experimental design. Currently there are built in support for models developed with 'Repast Simphony' Agent-Based framework (<https://repast.github.io/>) and with NetLogo (<https://ccl.northwestern.edu/netlogo/>) which are the most used frameworks for Agent-based modeling.
Maintained by Antonio Prestes Garcia. Last updated 5 years ago.
6 stars 3.92 score 28 scripts