0
  • DE
  • EN
  • FR
  • International Database and Gallery of Structures

Advertisement

Performance Assessment of Metaheuristic Algorithms for Structural Optimization Taking Into Account the Influence of Algorithmic Control Parameters

Author(s):


Medium: journal article
Language(s): English
Published in: Frontiers in Built Environment, , v. 7
DOI: 10.3389/fbuil.2021.618851
Abstract:

Metaheuristic optimization algorithms are strongly present in the literature on discrete optimization. They typically 1) use stochastic operators, making each run unique, and 2) often have algorithmic control parameters that have an unpredictable impact on convergence. Although both 1) and 2) affect algorithm performance, the effect of the control parameters is mostly disregarded in the literature on structural optimization, making it difficult to formulate general conclusions. In this article, a new method is presented to assess the performance of a metaheuristic algorithm in relation to its control parameter values. A Monte Carlo simulation is conducted in which several independent runs of the algorithm are performed with random control parameter values. In each run, a measure of performance is recorded. The resulting dataset is limited to the runs that performed best. The frequency of each parameter value occurring in this subset reveals which values are responsible for good performance. Importance sampling techniques are used to ensure that inferences from the simulation are sufficiently accurate. The new performance assessment method is demonstrated for the genetic algorithm inmatlabR2018b, applied to seven common structural optimization test problems, where it successfully detects unimportant parameters (for the problems at hand) while identifying well-performing values for the important parameters. For two of the test problems, a better solution is found than the best solution reported so far in the literature.

Copyright: © 2021 Wouter Dillen, Geert Lombaert, Mattias Schevenels
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10603667
  • Published on:
    17/04/2021
  • Last updated on:
    02/06/2021