A Systematic Study on Solving Aerospace Problems Using Metaheuristics

TL;DR

This paper systematically reviews how metaheuristics are applied to solve various complex aerospace engineering problems, identifying popular algorithms, hybridizations, and problem types based on literature up to March 2022.

Contribution

It provides a comprehensive overview of metaheuristic applications in aerospace, highlighting prevalent algorithms, hybrid approaches, and problem classifications in the field.

Findings

Metaheuristics are widely used in aerospace optimization problems.

Hybrid algorithms are frequently employed for complex aerospace tasks.

Certain algorithms dominate specific problem types in aerospace applications.

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.