Topic: "hyperheuristic"
jcrvz/customhys
Customising optimisation metaheuristics via hyper-heuristic search (CUSTOMHyS). This framework provides tools for solving, but not limited to, continuous optimisation problems using a hyper-heuristic approach for customising metaheuristics. Such an approach is powered by a strategy based on Simulated Annealing. Also, several search operators serve as building blocks for tailoring metaheuristics. They were extracted from ten well-known metaheuristics in the literature.
Language: Python - Size: 52 MB - Last synced at: 18 days ago - Pushed at: 5 months ago - Stars: 22 - Forks: 12
seage/seage
SEAGE (Search Agents) is a hyper-heuristic framework for metaheuristic collaboration.
Language: Java - Size: 17.2 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 9 - Forks: 6
g-soto/HHNN
Neural network applied as hyper-heuristics to the knaspack problem.
Language: Python - Size: 232 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 1 - Forks: 0
AndresGarciaEscalante/Fire-Fighter-Problem Fork of jcobayliss/FFPHHS
Our approach uses a Fuzzy Hyper Heuristic model for solving the Fightfighter problem. However, we mainly focus in the fuzzification stage, where we provide three different models using triangular, trapezoidal, and gaussian member functions to represent the features.
Language: Jupyter Notebook - Size: 2.07 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 0
