Advances in Optimization Algorithms and Its Applications

Dear Colleagues,

As the landscape of technological advancements continues to evolve at an unprecedented pace, the demand for efficient and effective optimization algorithms has grown exponentially across diverse engineering domains. These algorithms play a pivotal role in solving complex real-world problems, ranging from resource allocation and system design to parameter tuning and decision-making processes. Recognizing this need, the field of optimization algorithms has witnessed significant advancements, with bio-inspired approaches emerging as a prominent category due to their innate ability to mimic the dynamic and intelligent behaviors observed in nature.

The Special Issue, titled "Advances in Optimization Algorithms and Its Applications", will consolidate the latest research endeavors that have pushed the boundaries of optimization methodologies, particularly those inspired by biological systems. By harnessing the power of evolutionary processes, swarm intelligence, and other natural phenomena, these algorithms demonstrate remarkable potential in tackling intricate challenges characterized by non-convexity, nonlinearity, high dimensionality, and stringent constraints.

This Special Issue invites submissions from researchers worldwide, showcasing cutting-edge works that contribute to the theoretical foundations and practical applications of optimization algorithms. Contributions are sought to cover a broad spectrum of topics, including but not limited to the following:

Novel Bio-inspired Optimization Algorithms: Presentations of new optimization algorithms inspired by biological systems, such as genetic algorithms, particle swarm optimization, ant colony optimization, and artificial neural networks, with a focus on their unique mechanisms, performance enhancements, and theoretical analyses.

Hybrid and Multi-objective Optimization: Investigations into the fusion of bio-inspired algorithms with traditional optimization techniques or among different bio-inspired approaches, as well as strategies for solving multi-objective optimization problems, balancing conflicting objectives, and achieving Pareto optimality.

Applications in Engineering and Beyond: Demonstrations of how these advanced optimization algorithms are being applied to solve pressing engineering problems in areas like aerospace, the automotive industry, civil engineering, energy systems, and manufacturing. Additionally, explorations of their potential in other disciplines, such as finance, healthcare, and environmental management, are also encouraged.

Performance Evaluation and Benchmarking: Comparative studies evaluating the performances of bio-inspired optimization algorithms on standard and real-world benchmarks, highlighting their strengths, weaknesses, and suitability for specific problem types.

Computational Intelligence and Machine Learning Integration: Discussions on how computational intelligence techniques, including machine learning and deep learning, can be integrated with optimization algorithms to further enhance their capabilities and adaptability.

By featuring high-quality research in these and related areas, this Special Issue will foster interdisciplinary collaboration, promote knowledge sharing, and inspire future directions in the ever-evolving field of optimization algorithms and their applications.

Prof. Dr. Heming Jia
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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 optimization algorithms
• optimization algorithms
• meta-heuristics
• swarm intelligence
• engineering applications
• engineering design problems
• real-world applications
• feature selection
• image segmentation
• constraint handling
• benchmarks
• novel approaches
• complicated optimization problems
• industrial problems