27 lines
1.7 KiB
Markdown
27 lines
1.7 KiB
Markdown
# Plan After Literature Review
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After reading the papers in the Google Drive (see `paper_notes.md`) I've come up with the following
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plan:
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I think that I'd like to follow an approach similar to what I saw in Englander and Morante. However,
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I think it makes more sense to follow the Englander approach for the specific optimizers being used
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in the inner and outer loops. Specifically this means:
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- Set up the problem as a Hybrid Optimal Control Problem (HOCP) with an inner and an outer loop
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- The outer loop will determine the number and identities of the flybys and optimize using a Binary
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Genetic Algorithm described by Englander
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- The inner loop in Englander uses Sims-Flanagan Transcription optimized using monotonic basin
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hopping. This seems like a good approach. I'd like to use this approach, but also consider using,
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as an alternative method for comparison, one of the machine-learning algorithms from the other
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papers.
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- There are a number of other details including modeling launch C3, power, thrust, and ephemeris.
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For all of these I'll use either the exact approach from Englander or a similar approach. There
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exists an option to use alternatives to SPICE for ephemeris, but I think the parallelization
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problems that SPICE poses can be solved in other ways.
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- Specifically, I'd like to build this program using a micro-service architecture. This could
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allow for deployment using Kubernetes clusters. This will handle the parallelization (by
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running multiple inner loop micro-services at once) and allow for simpler use in production
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environments if that's ever needed, as kubernetes has a robust integration with most
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web-hosting services. This also allows for flexible scalability if improved speed is ever
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needed.
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