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geneticalgorithmproject's Introduction

A Framework for Self-Adaptive Genetic Algorithms

Master's Thesis By Benjamin Eriksen

Overview

This folder contains the thesis itself, along with the program developed. The folders are structured as described in the following subsections.

framework

Contains the framework for implementing and testing gentic algorithms. The details about the structure is found in the thesis report.

results

Contains the final results of the testing done in the folder final. These are arranged into files by the name of the problem and for some the external source of the problem instances. Contains all plots used in the thesis report in the plots folder.

documentation

Contains other plots and figures used in the thesis report.

problems

Contains problem instances for TSP and 3-SAT problems. The sources are a subset of the problems available on TSPLIB and a subset of the Uniform Random-3-SAT collection from SATLIB. It also contains the optimal solutions for TSP instances, which are used to generate the goal.

scripts

Contains the script for generating the test data used in the thesis report.

data_analysis

Contains python scripts to manage results and generate plots.

How to run

The external Makefile can be used to activate any of the test scipts used to generate the data for the thesis report(Beware! The running time is quite extensive).

make [onemax/leadingones/jumpm/tsn/3sat]

Alternatively the program can be run through the terminal. A few examples a shown below.

python3 src/main.py --problem OneMax --size 500 --goal 500 --time_limit 10 --algorithm ["GADynamic"] --sample_size 15
python3 framework/src/main.py --problem Sorting --size 10 --goal $n --SD_RLS_R 11 --time_limit 15 --algorithm ["GABE1,GABE2,GAAdaptiveMut,SD_RLS"] --mutation_operator k-swap --sample_size 15
python3 framework/src/main.py --problem ThreeSAT --problem_file uf20-018.cnf --time_limit 60 --sample_size 2 --algorithm ["GABE1,GABE2,GAAdaptiveMut,SD_RLS,GAStatic,GADynamic,GAStandard"] --SD_RLS_R 90

Results

OneMax

OneMax: Average Score OneMax: Computational Complexity OneMax: Running Time

LeadingOnes

LeadingOnes: Average Score LeadingOnes: Computational Complexity LeadingOnes: Running Time

JumpM

JumpM: Average Score JumpM: Computational Complexity JumpM: Running Time

3-Sat

3-Sat: Average Score 3-Sat: Computational Complexity 3-Sat: Running Time

TSP

TSP: Average Score

Sorting

Sorting: Average Score

SwapSorting

SwapSorting: Average Score

geneticalgorithmproject's People

Contributors

benjamineriksen95 avatar

Watchers

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