Added initial notes

prelim_notes/plan.md

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+# 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.