Pedrammehr, Siamak, and Chalak Qazani, Mohammad Reza (2024) Special Issue “Optimisation Models and Applications”. Axioms, 13 (1). 45.

Preview

PDF (Published Version) - Published Version Available under License Creative Commons Attribution. Download (151kB) | Preview

Abstract

[Extract] Optimisation models have transcended their origins to become indispensable tools across many fields, including engineering, economics, the environment, health, systems of systems, businesses, and beyond. These models serve as guiding lights, illuminating the path toward optimal solutions. Within the optimisation realm, the following four distinct categories emerge, akin to constellations in the scientific cosmos: physics-based optimisation algorithms, swarm-based optimisation algorithms, game-based optimisation algorithms, and evolutionary-based optimisation algorithms. Over the past half-century, the optimisation domain has been a crucible where theory meets practice, generating solutions that have left indelible marks on diverse applications. In this Special Issue, our study takes us to the heart of the intricate interplay between optimisation models and their practical applications. In this realm, theory and reality merge to address fundamental scientific challenges. We earnestly invite researchers, akin to celestial navigators, to contribute their original, high-quality research papers. Let us explore the celestial expanse of optimisation and its transformative applications.

Item ID:	86718
Item Type:	Article (Editorial)
ISSN:	2075-1680
Copyright Information:	© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Date Deposited:	14 Oct 2025 03:48
FoR Codes:	49 MATHEMATICAL SCIENCES > 4903 Numerical and computational mathematics > 490304 Optimisation @ 100%
SEO Codes:	28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280110 Expanding knowledge in engineering @ 30% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 70%
Downloads:	Total: 60 Last 12 Months: 24
	More Statistics