application of optimization Using AI
Budget: $30 – $250 USD
Choose a topic of your interest related to any application of optimization, and submit a final report in the form of a slide deck. Your project could be theory or implementation-oriented.
Examples of topics are the optimal distribution of covid vaccines, the best pairing of wines with foods, robot search and rescue planning, drone video analytics, natural language processing-based mental health classifier, AI-driven wireless networking, spatial data analysis, and geospatial data analytics.
Format:
---Title slide
---Problem Description (high-level, plain English description of the problem; why it is important?)
---Optimization Model (objective function, constraints; explain the rationale behind your model)
---Proposed Solution (is it convex/non-convex?; what is the feasible set?; why you concluded a solution may exist; closed-form solution; numerical solution using a toolbox, etc.)
---Validating Solution (how did you test your solution is valid, e.g., tested using dataset, simulations, theoretical analysis, etc.)
---Key Insights (what does your solution mean for the problem? what are the key observations you made from the solutions as applied to the problem?)
---Major Conclusions (was your approach viable?, did you run into any difficulties such as infeasibility, numerical instability, unexpected results, etc.)
(Please don't use others work)
Examples of topics are the optimal distribution of covid vaccines, the best pairing of wines with foods, robot search and rescue planning, drone video analytics, natural language processing-based mental health classifier, AI-driven wireless networking, spatial data analysis, and geospatial data analytics.
Format:
---Title slide
---Problem Description (high-level, plain English description of the problem; why it is important?)
---Optimization Model (objective function, constraints; explain the rationale behind your model)
---Proposed Solution (is it convex/non-convex?; what is the feasible set?; why you concluded a solution may exist; closed-form solution; numerical solution using a toolbox, etc.)
---Validating Solution (how did you test your solution is valid, e.g., tested using dataset, simulations, theoretical analysis, etc.)
---Key Insights (what does your solution mean for the problem? what are the key observations you made from the solutions as applied to the problem?)
---Major Conclusions (was your approach viable?, did you run into any difficulties such as infeasibility, numerical instability, unexpected results, etc.)
(Please don't use others work)