MEALPY

MEALPY [1] is a Python library for the most of cutting-edge population meta-heuristic algorithms - a field which provides an fast and efficient way to find the global optimal point of mathematical optimization problems.

The MEALPY library has been integrated into numgeo-ACT in such a way that it is very easy to access different algorithms for optimization via a simple interface. To access this interface, the MEALPY module must first be imported from numgeo-ACT:

import ACT.mealpy as ACTmealpy

Then (after some more steps to read in the experimental data and choose the constitutive model and the weighting factors) the calibration of the constitutive model parameters can be started via the following interface:

...
ACTmealpy.optimize(maxiter=300, n_cpu=32, method='DifferentialEvolution')

The interface has five optional arguments:

• maxiter: Maximum number of iterations to be performed before the optimization stops, default is maxiter=200.
• exit_iter: Early stoppage criterion. If the global best solution not better an epsilon after exit_iter iterations then stop the optimization. Default is exit_iter=30
• popsize: Population size defined as the next power to two of N*popsize, where N is the dimensionality of the problem (= number of parameters of the constitutive model to be optimized). Default is popsize=15.
• method : Optimization algorithm to be used. Currently the following algorithms are:
  • ArithmeticOptimization, see Arithmetic Optimization
  • CrossEntropy, see Cross-Entropy Method
  • DifferentialEvolution, see Differential Evolution
  • DifferentialEvolution-JADE, see Differential Evolution - JADE
  • DifferentialEvolution-LSHADE, see Differential Evolution - LSHADE
  • GeneticAlgorithm, see Genetic Algorithm
  • GradientBased, see Gradient Based Optimization
  • ParticleSwarmOptimization-CL, see Particle Swarm Optimization - Comprehensive Learning
  • ParticleSwarmOptimization-TVAC, see Particle Swarm Optimization Hierarchical Time-Varying Acceleration

References

[1] N. V. Thieu and S. Mirjalili, ‘MEALPY: a framework of the state-of-the-art meta-heuristic algorithms in python’. Zenodo, Jun. 2022. doi: 10.5281/zenodo.6684223.