P||CMax_genetic_algorytm

Solution of P-CMax problem using genetic algorythm

How to run the program

• clone the repository
• run main.py with 2 parameters
  • first
    • genetic if you want to use genetic algorythm
    • greedy if you want to use greedy algorythm
  • second - file path
• example python main.py genetic ./data./m50n1000.txt

How to choose data

You can choose ready data from data folder or use the data generator

What is the P||CMax problem in computer science

In the P || Cmax problem, the task is to arrange 𝑛 tasks on 𝑚 processors in such a way that the completion time of all tasks on all processors is as short as possible.

What is a genetic algorithm?

In computer science and operations research, a genetic algorithm is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms. Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems by relying on biologically inspired operators such as mutation, crossover and selection.