ACM Transactions on Evolutionary Learning and Optimization (TELO) to be Covered in Elsevier’s Scopus Database
New York, NY, October 5, 2023 — ACM, the Association for Computing Machinery, is pleased to announce that its Transactions on Evolutionary Learning and Optimization (TELO) has been selected to be included in Elsevier’s Scopus abstract and indexing database. By having its content included in Scopus, TELO’s content will be discoverable at 7,000 of the world’s top research institutions. Inclusion in Scopus is highly competitive and is determined by a panel of independent subject matter experts.
Launched in 2004, Scopus covers nearly 36,400 journals from approximately 11,678 publishers.
In accepting TELO for the Scopus database, curators considered factors such as TELO’s location in an interesting and active area of research, the number of quality articles the journal has attracted, the number of citations to the journal, and the strength of its editorial board. All journals covered in the Scopus database are reviewed for sufficiently high quality each year according to four types of numerical quality measure for each title; h-Index, CiteScore, SJR (SCImago Journal Rank), and SNIP (source normalized impact per paper).
“Typically, academic research journals invited to join Scopus have built a reputation in their respective research areas over several years,” commented ACM Director of Publications Scott Delman. “The inaugural issue of TELO, by contrast, was just published in June 2021, so TELO achieved this distinction in less than three years. We congratulate Co-Editor-in-Chiefs Juergen Branke from the University of Warwick, and Manuel López-Ibáñez from the University of Manchester, as well as the entire TELO Editorial Board. We also look forward to bringing more ACM journals into the Scopus family in the near future.”
About ACM TELO
ACM Transactions on Evolutionary Learning and Optimization publishes original papers in all areas of evolutionary computation and related areas such as evolutionary machine learning, evolutionary reinforcement learning, Bayesian optimization, evolutionary robotics and other metaheuristics.
The editors welcome papers that make solid contributions to theory, method and applications. Relevant domains include continuous, combinatorial or multi-objective optimization. Applications of interest include but are not limited to logistics, scheduling, healthcare, games, robotics, software engineering, feature selection, and clustering as well as the open-ended evolution of complex systems.
The editors are particularly interested in papers at the intersection of optimization and machine learning, such as the use of evolutionary optimization for tuning and configuring machine learning algorithms, machine learning to support and configure evolutionary optimization, and hybrids of evolutionary algorithms with other optimization and machine learning techniques. ACM TELO encourages reproducibility.
About ACM Journals
ACM publishes more than 60 scholarly peer-reviewed journals in dozens of computing and information technology disciplines. Available in print and online, ACM's high-impact, peer-reviewed journals constitute a vast and comprehensive archive of computing innovation, covering emerging and established computing research for both practical and theoretical applications. ACM journal editors are thought leaders in their fields, and ACM's emphasis on rapid publication ensures minimal delay in communicating exciting new ideas and discoveries.
About ACM
ACM, the Association for Computing Machinery, is the world's largest educational and scientific computing society, uniting educators, researchers, and professionals to inspire dialogue, share resources, and address the field's challenges. ACM strengthens the computing profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.
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