Journal of optimization and artificial intelligence

JOAI is an open-access journal dedicated to advancing the fields of optimization, informatics, and artificial intelligence (AI). It covers a broad range of topics, including combinatorial optimization, computer science security, computational complexity, informatics, computational intelligence, grid computing, meta-heuristic algorithms, operations research, semantic web, software engineering, and various aspects of web technologies. Additionally, JOAI now extends its focus to encompass emerging areas within AI, such as deep learning, reinforcement learning, explainable AI, AI ethics, AI applications in healthcare, finance, natural language processing, robotics, Internet of Things (IoT), and smart cities. Researchers and practitioners are encouraged to contribute their original work to facilitate the dissemination of knowledge and advancements in these fields.

the journal will soon be evaluated by scopus for indexing. 

Topics: Advancements in Optimization, Machine Learning, and Artificial Intelligence

Optimization Algorithms

• Metaheuristic optimization
• Evolutionary algorithms
• Swarm intelligence
• Genetic algorithms
• Ant colony optimization
• Particle swarm optimization

Machine Learning Models

• Deep learning architectures
• Neural networks
• Reinforcement learning
• Ensemble learning
• Transfer learning
• Explainable AI

Artificial Intelligence Applications

• Natural Language Processing (NLP)
• Computer vision
• Speech recognition
• Robotics and automation
• Recommender systems
• Intelligent agents and multi-agent systems

Optimization in Data Science

• Data preprocessing and cleaning
• Feature selection and extraction
• Model selection and hyperparameter tuning
• Model interpretation and evaluation
• Handling imbalanced data

Applications of AI in Specific Domains

• Healthcare and medical diagnostics
• Finance and investment strategies
• Agriculture and precision farming
• Smart cities and urban planning
• Environmental monitoring and sustainability

Hybrid Models

• Integration of optimization and machine learning
• Hybrid AI systems
• Neuro-symbolic systems
• Fuzzy logic and AI

General Journal guidelines

General Journal guidelines for authors Journal of optimization and artificial intelligence publishes research articles, reviews, short communications, and case studies. Research articles must include: motivation for the work, an adequate overview of the representative work in the field including up-to-date references, a clear statement of the novelty in the presented research, suitable theoretical background, one or more examples to demonstrate and discuss the presented ideas and, finally, conclusions. Short communications are usually 4-7 pages long, research articles and case studies 8-14 pages, while reviews can be longer. Page number limits are not strict and, with appropriate reasoning, the submitted articles can also be longer or shorter. Authors are requested to follow the Journal of optimization and artificial intelligence guidelines and strictly format their manuscripts as per the article template that is available here. If extensions of previously published conference papers are submitted, Editors will check if sufficient new material has been added to fulfill the journal standards and qualify the submission for the review process. The added material must not have been previously published. New results are desired but not necessarily required; however, the submission should contain expansions of key ideas, examples, elaborations, etc. of the conference submission.

Aims and Scope: The principal aim of the journal is to bring together the latest research and development in various fields of intelligent systems, ombinatorial optimization, computer science security, computational complexity, informatics, computational intelligence, grid computing, meta-heuristic algorithms, operations research, semantic web, software engineering, various aspects of web technologies, and artificial intelligence.

We would like to highlight that papers should refer to Aims and scope, but they are not limited to. Publication Frequency: One issue per year is published online, but processed and accepted papers, with full bibliographic data, are added to the issue continuously over the whole year.

Open Access: This is an open-access journal which means that all content is freely available without charge to the user or his/her institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without asking prior permission from the publisher or the author.

Publication fee: Free of charge.

Special issue (ICOMA 2024 , Conference)

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 Introduction:

Welcome to the International Conference on Advances in Optimization, Machine Learning and Artificial Intelligence (ICOMA). This conference provides an invaluable platform for exploring the crucial role of optimization, machine learning and artificial intelligence in the ever-changing landscape of computational science. By bringing together researchers, academics and practitioners from around the world, ICOMA fosters a vibrant and stimulating interdisciplinary dialogue that fuels innovation.