Biogeography-Based Optimization (BBO) in MATLAB
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Updated
Dec 5, 2020 - MATLAB
Biogeography-Based Optimization (BBO) in MATLAB
Experiments from the paper "A diversity metric for population-based metaheuristic algorithms", published in 2022.
Implementation of genetic algorithms with matlab
Experiments from the paper "Optimal control strategy based on neural model of nonlinear systems and evolutionary algorithms for renewable energy production as applied to biofuel generation", published in 2017.
MATLAB code for Teaching Learning Based Optimization Algorithm (minimization and maximization)
Strength Pareto Evolutionary Algorithm 2 (SPEA2) in MATLAB
Assignment 1 of EC2021 (Evolutionary-Computation-and-Its-Applications)
A simplified and effective version of IPO (called SIPO) with the aim of simplifying the main IPO equations, creating a powerful trade-off between the concepts of exploitation and exploration, and modifying the complexity of their structural parameters.
Solving the Travelling salesman problem using genetic algorithms in Matlab.
Assignments and Classworks for evolutionary computing for Summer Semester 2018 at Hochschule Bonn-Rhein-Sieg
Imperialist Competitive Algorithm (ICA) in MATLAB
FAEICA-Algorithm (Fuzzy adaptive optimisation method)
FuzzyMSFLA-Algorithm (Fuzzy adaptive optimisation method)
FBGA-MLP model (hybrid machine learning model)
A genetic algorithm variant to run parallel populations to save time while acting similar to the original one
A pure-MATLAB library of EVolutionary (population-based) OPTimization for Large-Scale black-box continuous Optimization (evopt-lso).
Some evoluationary algorithms (e.g., genetic algorithm and water flow optimizer) using GPU.
With the aim of create a powerful trade-off between the concepts of exploitation and exploration, and rectify the complexity of their structural parameters in the standard IPO, a modified version of IPO (called MIPO) is introduced as an efficient optimization algorithm for digital infinite-impulse-response (IIR) filters model identification. The…
The optimization field suffers from the metaphor-based “pseudo-novel” or “fancy” optimizers. Most of these cliché methods mimic animals' searching trends and possess a small contribution to the optimization process itself. Most of these cliché methods suffer from the locally efficient performance, biased verification methods on easy problems, an…
MultiObjectiveFAEICA-Algorithm (Multi-objective fuzzy adaptive optimisation approach)
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