and to submit
ACM Transactions on Evolutionary Learning and Optimization
( TELO) publishes high-quality, original papers in all areas
of evolutionary computation and related areas such as
population-based methods, Bayesian optimization, or
We 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, clustering as well as the
open-ended evolution of complex systems.
We are particularly interested in papers at the intersection
of optimization and machine learning, such as the use
of evolutionary optimization for tuning and con;guring
machine learning algorithms, machine learning to support
and con;gure evolutionary optimization, and hybrids
of evolutionary algorithms with other optimization and
machine learning techniques.
Publishes;papers at the intersection of optimization
ACM Transactions on
and machine learning, making;solid contributions to
theory, method and applications in the ;eld.
and Optimization (TELO)