In the GA programming environment, since the performance of
the GA is greatly influenced by the defined parameters (i.e. population
size, iteration number, crossover rate (CR) and mutation rate
(MR)), many combinations with different values for each parameter
were tested to arrive at an optimal solution.The parameters for the
GA were Pop Size ¼ 800, iteration number = 200, CR ¼ 0:6, and
MR ¼ 0:2. After running the program over 20 times for the p-based