Spontaneous Fruit Fly Optimisation for truss weight minimisation: Performance evaluation based on the no free lunch theorem

TL;DR

This paper introduces Spontaneous Fruit Fly Optimisation (s-FOA), a simplified and robust algorithm for truss weight minimisation, evaluated on benchmark problems and compared favorably with existing methods.

Contribution

The paper presents s-FOA, an improved, parameter-standardised version of c-FOA, designed to perform well across various nonlinear optimisation problems with minimal tuning.

Findings

s-FOA outperforms existing algorithms on benchmark problems

s-FOA demonstrates robustness and efficiency in truss optimisation

The method requires standard parameters and small population size

Abstract

Over the past decade, several researchers have presented various optimisation algorithms for use in truss design. The no free lunch theorem implies that no optimisation algorithm fits all problems; therefore, the interest is not only in the accuracy and convergence rate of the algorithm but also the tuning effort and population size required for achieving the optimal result. The latter is particularly crucial for computationally intensive or high-dimensional problems. Contrast-based Fruit-fly Optimisation Algorithm (c-FOA) proposed by Kanarachos et al. in 2017 is based on the efficiency of fruit flies in food foraging by olfaction and visual contrast. The proposed Spontaneous Fruit Fly Optimisation (s-FOA) enhances c-FOA and addresses the difficulty in solving nonlinear optimisation algorithms by presenting standard parameters and lean population size for use on all optimisation problems. Six benchmark problems were studied to assess the performance of s-FOA. A comparison of the results obtained from documented literature and other investigated techniques demonstrates the competence and robustness of the algorithm in truss optimisation.