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Course project for UW Math 381 Autumn 2018. Implemented and compared Stable Matching, Hungarian and Maximal Matching Algorithm on assigning student candidates to teaching assistant positions.

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Optimization of Matching

note: this project runs based on random generated data

Usage 1

Generate an assignment/matching between random generated student candidates and professors as well as their perferences to each other. Due to the lack of data, the course capacity is also random generated between 1 to 5.

py methods.py --num_candidate m --num_course n

where m= number of candidates you would like to have and n= number of courses you would like to have.

And choose the method you would like to use - s:stable_marriage, h:Hungarian, m:maximum_matching

Then enter the file name you would like to save as. Please end with .csv

Usage 2

Compare different methods based on Monte Carlos Simulation and plot out figures into the folder figures\numOfCandidates_numOfCourse_numOfSimulations

py methods.py --num_candidate m --num_course n --if_figure True

And enter the number of simulations you would like to have. A number greater than 100 is suggested.

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Course project for UW Math 381 Autumn 2018. Implemented and compared Stable Matching, Hungarian and Maximal Matching Algorithm on assigning student candidates to teaching assistant positions.

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