This work proposes an object-oriented unified optimization framework (UOF) for general problem optimization. Based on biological inspired techniques, numerical deterministic methods, and C++ objective design, the UOF itself has significant potential to perform optimization operations on various problems. The UOF provides basic interfaces to define a general problem and generic solver, enabling these two different research fields to be bridged. The components of the UOF can be separated into problem and solver components. These two parts work independently allowing high-level code to be reused, and rapidly adapted to new problems and solvers. The UOF is customized to deal with several optimization problems. The first experiment involves a well-known discrete combinational problem, wihle the second one studies the robustness for the reverse modeling problem, which is in high demanded by device manufacturing companies. Additionally, experiments are undertaken to determine the capability of the proposed methods in both analog and digital circuit design automation. The final experiment designs antenna for rapidly growing wireless communication. Most experiments are categorized as simulation-based optimization tasks in the microelectronics industry. The results confirm that UOF has excellent flexibility and extensibility to solve these problems successfully. The developed open-source project is publicly available.
- Biological inspired techniques
- Design automation
- Deterministic method
- Simulation-based optimization