A Systematic Study on Solving Aerospace Problems Using Metaheuristics

TL;DR

A systematic study on applying metaheuristics in aerospace based on the literature finds which classes of algorithms are most used in each problem and which classes of algorithms are most used in each problem.

Abstract

Complex engineering problems can be modelled as optimisation problems. For instance, optimising engines, materials, components, structure, aerodynamics, navigation, control, logistics, and planning is essential in aerospace. Metaheuristics are applied to solve these optimisation problems. The present paper presents a systematic study on applying metaheuristics in aerospace based on the literature. Relevant scientific repositories were consulted, and a structured methodology was used to filter the papers. Articles published until March 2022 associating metaheuristics and aerospace applications were selected. The most used algorithms and the most relevant hybridizations were identified. This work also analyses the main types of problems addressed in the aerospace context and which classes of algorithms are most used in each problem.

Figures (12)

• Figure 1: Word cloud built using the first 50 most frequent words in the title and keywords of the article defined by the authors and the journal.
• Figure 2: Articles remaining after each filtering phase.
• Figure 3: Evolution of the number of articles found in each database by year. The black bar represents the evolution of the selected papers after filtering.
• Figure 4: Box plot of the metaheuristics used in the selected papers. The review/survey articles show much more citations, but the median and average of the metaheuristics used are practically the same.
• Figure 5: Metaheuristics in the selected papers.