Comparative performance of meta-heuristic algorithms for mass minimisation of trusses with dynamic constraints

             

Comparative performance of meta-heuristic algorithms for mass minimisation of trusses with dynamic constraints

Abstract

This paper investigates the search performances of various meta-heuristics (MHs) for solving truss mass minimisation with dynamic constraints. Several established MHs were used to solve five truss optimisation problems. The results obtained from using the various MHs were statistically compared based upon convergence rate and consistency. It was found that the best optimisers for this design task are evolution strategy with covariance matrix adaptation (CMAES) and differential evolution (DE). Furthermore, the best penalty function technique was discovered while four penalty function techniques assigned with several parameter settings were used in combination with the five best optimisers to solve the truss optimisation problems.

Keywords

  • Meta-heuristics comparative performance;
  • Truss minimisation;
  • Dynamic constraints;
  • Evolutionary algorithms;
  • Shap and sizing optimisation;
  • Penalty function techniques

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