About

This repository contains the source code of my bachelor thesis with the name "Optimization of the placement of the charging stations for the electric vehicles". The thesis was written during my studies in the Faculty of Mathematics and Physics in the Charles University in Prague. The text of the thesis could be found in the repository bcs-thesis (note that the text is written in Czech).

Structure of The Repository

The repository contains multiple files and directories with the specific content. The repository contains:

• analysis_results/ - directory which contains information about the experiments and its results
• experiment_analysis/ - directory which contains programs for preparation of the scripts to run the experiments and display the output data
• map_preprocessing/ - directory which contains program for preparation of the input data for the traffic simulator
• prepared_grapg/ - directory which contains the prepared input data which represents the road network of the Czech Republic
• source_code/ - directory which contains the source code of the traffic simulator which is the main program of the thesis
• Traffic_Simulator_Manual.pdf - file with the development documentation generated from the comments in the source code (Note that more detailed documentation can be found in the text of the thesis here (only in Czech))

Abstract (EN)

As the number of electric vehicles grows, so does the need to create a suitable network of charging stations. A solution of this problem can be significantly improved by the usage of suitable optimization techniques. We implement a simplified traffic simulator serving as a suitable tool for their analysis. We also analyze optimization techniques using the so-called greedy algorithm, genetic algorithm and k-means algorithm. Based on the experiments, the optimizations using the genetic algorithm and the greedy algorithm showed noticeably better results. The k-means method did not show signs of results better than a random approach.

Abstract (CZ)

S rostoucím počtem elektrických vozidel roste i potřeba vytvořit vhodnou infrastrukturu pro jejich nabíjení. K řešení tohoto problému může výrazně napomoci použití vhodných optimalizačních metod. V práci jsme implementovali zjednodušený simulátor dopravy sloužící jako vhodný nástroj pro jejich analýzu. Analyzovali jsme také optimalizační metody tzv. hladovým algoritmem, genetickým algoritmem a algoritmem k-means. Na základě experimentů vykazovala prokazatelně lepší výsledky optimalizace za využití genetického algoritmu a hladová optimalizace. K-means optimalizace nevykazovala známky lepších výsledků oproti náhodnému přístupu.