- Modify configurations in
\src\com\yuhao\config\Constant.java- put the input instance file in correct place (e.g.
\resource\test_instance.txt) and configure the path to the input file and output folder - configure number of trials, random seeds to use, etc.
- do parameter tuning (e.g. innovation rate, crossover operator to use, etc.)
- detailed instruction of parameters can be found in
Constantclass
- put the input instance file in correct place (e.g.
- Build the whole project
- Run
mainmethod ofCourseworkRunnerin\src\com\yuhao\CourseworkRunner.java - The best solution and its objective value per trial can be found in the standard output; while the best/worst
objective value of the first
MAX_NUMBER_OF_ENTRIES_TO_WRITEloops per trial can be found in the output files
- IDE used for this project: IntelliJ IDEA or Eclipse
- Inspired by : Ender Ozcan et al., A Self-adaptive Multimeme Memetic Algorithm Co-evolving Utility Scores to Control Genetic Operators and Their Parameter Settings, pp. 11-13 ( Link: http://www.cs.nott.ac.uk/~pszeo/docs/publications/multimemeAlgorithmChesc.pdf)