Suppose, you are the owner of a bank that operates in a strange way. Customers can lend money from your bank (just like a normal bank) and they can also deposit money in your bank. A register is maintained to track the daily transactions. However, being the strange owner of a strange bank, you have a fascination with finding out whether a portion of your daily transactions (in/out) balance out to zero. For example, suppose your daily transaction register looks like this:
1 Lend 100
2 Deposit 150
3 Lend 400
4 Lend 500
5 Deposit 1000
6 Lend 460
7 Deposit 160
8 Deposit 200
9 Lend 500
10 Depost 100
In this case, there is a portion of the transactions that would balance itself out. (6th, 7th, 8th, and 10th transactions would amount to 0).
Your task is to use a genetic algorithm to solve this strange bank problem.
Task Breakdown:
1. Model the transaction register in a way suitable for the problem.
2. Write a fitness function. Hint: It is the sum of the non-zero elements of a register.
3. Write the crossover function.
4. Write the mutation function.
5. Create a population of randomly generated registers.
6. Run genetic algorithms on the population until highest fitness has been reached and/or number of maximum iterations has been reached. Input followed by 𝑁 lines each starting𝑁 with either l or d and a number 𝑆 denoting The first line has a number denoting the number of daily transactions
the amount of transaction. Here:
𝑁
Output𝑆 ( 1 𝑆 10 )
The output would be a binary string denoting the specific transactions that balance themselves to zero or -1 if such a string cannot be formed. String consisting of all zeros won’t be accepted.
Example:
Sample Input 1
7
l 120 l 289 d 475 l 195 d 6482 l 160 d 935
Sample Output 1
1011010
Sample Input 2
5
l 100 l 450 d 500 l 7923 d 9055
Sample Output 2
-1
