Basic Concepts and Background.- Fundamentals of Optimization Techniques in Analog IC Sizing.- High-Performance Analog IC Sizing: Advanced Constraint Handling and Search Methods.- Analog Circuit Sizing with Fuzzy Specifications: Addressing Soft Constraints.- Process Variation-aware Analog Circuit Sizing: Uncertain Optimization.- Ordinal Optimization-based Methods for Efficient Variation-aware Analog IC Sizing.- Electromagnetic Design Automation: Surrogate Model Assisted Evolutionary Algorithm.- Passive Components Synthesis at High Frequencies: Handling Prediction Uncertainty.- mm-Wave Linear Amplifier Design Automation: A First Step to Complex Problems.- mm-Wave Nonlinear IC and Complex Antenna Synthesis: Handling High Dimensionality.
Computational intelligence techniques are becoming more and more important for automated problem solving nowadays. Due to the growing complexity of industrial applications and the increasingly tight time-to-market requirements, the time available for thorough problem analysis and development of tailored solution methods is decreasing. There is no doubt that this trend will continue in the foreseeable future. Hence, it is not surprising that robust and general automated problem solving methods with satisfactory performance are needed.