Immigration is generally considered an option in genetic algorithms, but I have found immigration to be extremely useful in almost all situations where I use evolutionary optimization. The idea of ...

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and ...

Andes AutoOpTune™ is available as a separately licensable plugin of AndeSight™ v5.4 and supports all Andes RISC-V processors. Via simple option tuning and recompilation, developers can gain extra ...

Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, ...

Our inclusion of skewness and kurtosis makes portfolio optimization a nonlinear, nonconvex and multi-objective problem; this has been solved with the use of a genetic algorithm. Empirical results ...

A research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences has proposed a novel model optimization algorithm—External Calibration-Assisted Screening (ECA)— that ...

Zhang, H., Zeng, Y. & Bian, L. (2010) Simulating multi-objective spatial optimization allocation of land use based on the integration of multi-agent system and genetic algorithm.

Evolutionary optimization (EO) is a technique for finding approximate solutions to difficult or impossible numeric optimization problems. In particular, EO can be used to train a neural network. EO is ...