#2490 Second-Layer GA/GP for Meta-Optimization
#2490 Second-Layer GA/GP for Meta-Optimization #2490 I have a two-phase goal: First phase is to apply Genetic Algorithms (GA) and/or Genetic Programming (GP) to improve computer chip design. The second phase is to apply GA/GP to improving the first-phase GA/GP process For your two-phase goal, both phases can benefit from the same foundational concepts in Genetic Algorithms (GA) and Genetic Programming (GP), but with varying objectives. Phase 1: GA/GP for Improving Computer Chip Design Problem Representation : Use GA/GP to represent chip design parameters, such as architecture, layout, and logic gates. Each "individual" in the population could be a potential chip design or configuration, with variables like transistor layout, interconnect strategies, and even the use of multi-core architectures. Fitness Function : This should measure chip efficiency, power consumption, speed, and heat dissipation. You can also introduce constraints like manufacturing costs or physical size. Th