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Comparison of standard library functions and our own implementations of genetic algorithm, simulated annealing, and particle swarm optimization

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Optimization Project

Course project for AE755 [Optimization for Engineering Design], Spring 2021


Project Title

Design of Full Car Suspension Model to Maximize Rider Comfort

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Usage

git clone https://github.com/trunc8/optimization-project.git
cd optimization-project
pip3 install -r requirements.txt

To check help menu and find list of algorithms

python3 code/suspension_optimization.py -h

To run the script against, say, Simulated Annealing

python3 code/suspension_optimization.py -a SA

To view intermediate design variable values, set the verbose flag (note that this will hide the progress bar)

python3 code/suspension_optimization.py -a SA -v

The results are automatically written to csv file with the corresponding algorithm name in the results directory.
The suspension problem formulation is briefly discussed in our presentation document along with collation of the results, our recommendations, and learnings.

Finally, in order to compare performance of all algorithms against the test objective functions, execute

python3 code/testing.py

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Created with ❤️ by Siddharth

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Comparison of standard library functions and our own implementations of genetic algorithm, simulated annealing, and particle swarm optimization

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