In recent years, metaheuristics (MHs) have become important tools for solving hard optimization problems encountered in industry, engineering, biomedical science, and image processing, as well as in the theoretical field. Several different metaheuristics exist, and new ones are under constant development. One of the most fundamental principles in our world is the search for an optimal state. Therefore, choosing the correct method for solving an optimization problem can be crucial in finding the right solutions for a given optimization problem (unconstrained and constrained optimization problems).

There exist a diverse range of MHs for optimization. Optimization techniques have been used for many years in the formulation and solution of computational problems. Among the subjects to be considered are theoretical developments in MHs; performance comparisons of MHs; cooperative methods combining different types of approaches such as constraint programming and mathematical programming techniques; parallel and distributed MHs for multi-objective optimization; adaptation of discrete MHs to continuous optimization; dynamic optimization; software implementations; and real-life applications. Machine learning (ML) is a data analytics technique using computational methods. Recently MHs have been combined with several ML techniques to deal with different global and engineering optimization problems and also real-world applications. Finding an optimal solution or even sub-optimal solutions is not an easy task.

This Special Issue aims to collect innovative solutions and high-quality research papers in the field of metaheuristics and machine learning. Papers published in this Special Issue should describe original works in different topics in both science and engineering, such as metaheuristics, machine learning, soft computing, neural networks, multi-criteria decision making, energy efficiency, sustainable development, etc. This Special Issue will be of interest to researchers and academics working in optimization, computer modelling, engineering, image processing, renewable energy, suitable development, and biomedical fields. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Single and multi-objective optimization
• Engineering applications
• Image processing, pattern recognition, and data mining
• Biomedical science, bioinformatics, and healthcare applications
• Software engineering
• Wireless communications and IoT applications
• Modelling based on artificial intelligence
• Multi-criteria decision making
• Energy efficiency