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Tech-Stack: Python with the DEAP EA library. An evolutionary algorithm selects the optimal football team from a selection of 523 players.

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AverageHomosapien/Football-Team-Selection-Evolutionary-Algorithm

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Football Team Selection Evolutionary Algorithm

This was a 4th year coursework done as part of the Emergent Computing for Optimisation module.

Overview

The task was to select the best football team from a file of 523 football players. Each player was given a cost and a score associated with their skill level.

The output representation required was a 523 length binary string, with a 1 at the position of each player selected to be taken and a 0 at the position of each player not coming.

Approach

I fully detail my approach in the PDF file attached. I will summarise my approach taken below:

I used Python and the Deap library as this has a lot of pre-built EA functions inbuilt. Python is an extremely flexible and easy-to-write language.

I used Jupyter Notebooks as this allows rapid prototyping, quick evaluation and code to be run line by line, which is extremely useful in a Scientific setting.

I used Matplotlib to visualise and compare my operators in the report as it allows for quick and flexible graphing.

An example of some results:

comparison-of-mutation-operators comparison-of-mutation-operators

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Tech-Stack: Python with the DEAP EA library. An evolutionary algorithm selects the optimal football team from a selection of 523 players.

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