The ever-increasing complexity of problems arising engineering and science has motivated the development and application of novel design, solution, and analysis methodologies. In particular, computational intelligence based methods have proven to be effective in challenging settings, and have therefore been extensively applied
to such problems. Examples of such applications include nature-inspired single and multi-objective optimization, neural network based surrogate approximations, and data analysis assisted by machine learning, to name a few. Given the extensive research and application of such methods, the goal of this special session is to provide a
vivid forum for presenting recent advances in the domain of applied computational intelligence in systems engineering, both from theoretical and practical perspectives.

Topics of ACISE encompass, but are not limited to:
- Dedicated implementations of computational intelligence methods such as nature inspired optimization, neural networks, and fuzzy logic.
- Reduction of expensive evaluations (surrogates, variable-fidelity, fitness inheritance).
- Methods for multi-objective, constrained, or robust problems.
- Parallelization of algorithms (implementations on clusters, grids, parallel machines).
- Incorporation of expert systems and human-system interface.
- Data mining and statistical analysis as assistive tools.
- Examples and analysis of real-world applications in science and engineering.