Nature-Inspired Metaheuristic Optimization Algorithms 2025

Dear Colleagues,

Developing computationally efficient algorithms has been at the forefront of research and development in recent years. With the advent of big data, deep learning, and artificial intelligence (AI), prioritizing computationally efficient software and hardware systems has become a primary design objective. Optimization algorithms are an integral part of all real-world systems. Although traditional gradient-based optimization methods have been rigorously studied over the years, they put several analytical constraints on the objective function, e.g., continuity, differentiability, and convexity. Additionally, an analytical model of the system should be a priori, which can be difficult to formulate for several real-world systems. These algorithms also do not apply to discontinuous and discrete systems. Even if the analytical model is known to be continuous and differentiable, the computational requirement of gradient and Hessians makes them expensive to implement.

Metaheuristic optimization algorithms inspired by natural processes and the behavior of biological organisms present themselves as an effective alternative to the traditional gradient-based algorithms. They have also been extensively explored in recent years and are rapidly finding applications in real-world systems. These algorithms are formulated on the principles of biomimetics, i.e., mimicking the behavior of biological systems to solve an optimization problem. The behavior of biological organisms has been optimized over millions of years through the process of natural selection. Every species has developed traits (mostly instinctual) necessary for survival in nature. Modeling this behavior as a mathematical algorithm presents great potential in regard to developing computationally efficient optimization algorithms. For example, evolutionary algorithms (EAs) and genetic algorithms (GAs) are inspired by the process of genetic mutations and the survival of the fittest. Similarly, other algorithms, like the particle swarm optimizer (PSO), gray wolf optimizer (GWO), and beetle antennae search (BAS) are inspired by the behavior of birds and insects and their ability to accomplish a task in a decentralized manner by just following their basic biological instincts and not needing any elaborate planning and centralized communication.

We are organizing this Special Issue to gather the latest research related to nature-inspired metaheuristic optimization algorithms and their applications. The application of a bio-inspired metaheuristic algorithm in real-world systems will draw greater research attention to biomimetics.

Dr. Ameer Hamza Khan
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomimetics is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• bio-inspired algorithms
• metaheuristic optimization
• gradient-free algorithms
• evolutionary algorithms (EAs)
• computational efficiency
• swarm intelligence

• Nature-Inspired Metaheuristic Optimization Algorithms 2024 in Biomimetics (31 articles)