thesis/prelim_notes/plan.md

Plan After Literature Review

After reading the papers in the Google Drive (see paper_notes.md) I've come up with the following plan:

I think that I'd like to follow an approach similar to what I saw in Englander and Morante. However, I think it makes more sense to follow the Englander approach for the specific optimizers being used in the inner and outer loops. Specifically this means:

• Set up the problem as a Hybrid Optimal Control Problem (HOCP) with an inner and an outer loop
• The outer loop will determine the number and identities of the flybys and optimize using a Binary Genetic Algorithm described by Englander
• The inner loop in Englander uses Sims-Flanagan Transcription optimized using monotonic basin hopping. This seems like a good approach. I'd like to use this approach, but also consider using, as an alternative method for comparison, one of the machine-learning algorithms from the other papers.
• There are a number of other details including modeling launch C3, power, thrust, and ephemeris. For all of these I'll use either the exact approach from Englander or a similar approach. There exists an option to use alternatives to SPICE for ephemeris, but I think the parallelization problems that SPICE poses can be solved in other ways.
  • Specifically, I'd like to build this program using a micro-service architecture. This could allow for deployment using Kubernetes clusters. This will handle the parallelization (by running multiple inner loop micro-services at once) and allow for simpler use in production environments if that's ever needed, as kubernetes has a robust integration with most web-hosting services. This also allows for flexible scalability if improved speed is ever needed.