Gen. No.

gap- Shuffle

random-insert-delete

1

-9553

-9526

5

-9469

-9526

30

-9446

-9474

50

-9363

-9458

100

-9363

-9362

500

-9340

-9362

1000

-9240

-9245

Table 2: Showing the variations in Fitness Score on changing the Mutation method.
(Results taken, while using Six input sequences, Single- Point Crossover, Gap Penalty=-2 as the remaining Input Parameters in the algorithm)