Review: Evolution of Nature-Inspired Metaheuristic Algorithms: Developments, Trends, and Applications from 1990 to 2025

Authors

  • Emem Ikpe1, * 1 VIT-AP University, Inavolu, Beside AP Secretariat, Amaravati AP, India‎., VIT-AP University, India‎.
  • Md. Faiaz Arman Talukdar Tonmoy2 2 Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh., Department of Industrial and Production Engineering, Bangladesh.

https://doi.org/10.48313/maa.vi.89

Abstract

This paper presents a comprehensive review of metaheuristic optimization algorithms across engineering and scientific domains over the period 2000-2025. We systematically analyze the literature on metaheuristic algorithms and their applications to engineering design, scheduling, machine learning, signal processing, c. The review covers approximately 165 papers, providing a structured taxonomy of algorithms, applications, and evaluation methodologies. We identify key trends including the shift toward hybrid approaches, integration of machine learning, and growing emphasis on explainability. The survey reveals that parameter tuning, premature convergence, scalability, benchmark fairne remain significant open problems. We provide detailed analysis of evaluation protocols, benchmark suites, and statistical methodologies. Future research directions include hybrid algorithm design, quantum-inspired methods, and standardized benchmarking frameworks.

Keywords:

metaheuristic optimization; general; review; survey; engineering design, scheduling, machine

Published

2026-08-13

Issue

Articles in Press

Section

Articles

How to Cite

Emem Ikpe1, & Md. Faiaz Arman Talukdar Tonmoy2. (2026). Review: Evolution of Nature-Inspired Metaheuristic Algorithms: Developments, Trends, and Applications from 1990 to 2025. Metaheuristic Algorithms With Applications. https://doi.org/10.48313/maa.vi.89