yongjiajun / Genetic-Algorithm-CLang

Project for Advanced Programming Techniques Assignment 2 [94/100%], RMIT University 2018

Genetic Algorithm

Project for Advanced Programming Techniques Assignment 2 [94/100%], RMIT University 2018

Implemented various advanced core functions in C language [ANSI / ISO C] such as gene mutation/crossover.

More info about the project can be found in the assignment spec, while other supporting documents can be found here.

*It's best to be compiled and ran on Linux.

To compile:

make

To run:

./ga geneType alleleSize popSize numGen inputFile [outputFile]

where:

• ./ga is the name of the executable

• geneType is a string, of either minfn or pcbmill – indicating which problem the GA is being applied to

• alleleSize is a positive non-zero integer specifying the length of a candidate solution (chromosome)

• popSize is a positive non-zero integer specifying the number of candidate solutions in the population

• numGen is a positive integer specifying the number of generations to run the GA for

• inputFile is a string specifying the name of a data file to read [either minfnin.dat or pcbin.dat]

• outputFile is an optional string specifying the name of an output file to write. If specified, there will be no console output but output will be stored into the output file.

For example:

./ga minfn 10 20 100 minfnin.dat

where:

• geneType = minfn
• alleleSize = 20
• popSize = 20
• numGen = 100
• inputFile = minfnin.dat
• outputFile = none

or

./ga pcbmill 10 20 100 pcbin.dat output.txt

where:

• geneType = pcbmill
• alleleSize = 10
• popSize = 20
• numGen = 100
• inputFile = pcbin.dat
• outputFile = output.txt

To cleanup:

make clean