Hands-On Genetic Algorithms with Python

Solution representation

When solving the knapsack 0-1 problem, a straightforward way to represent a solution is using a list of binary values. Every entry in that list corresponds to one of the items in the problem. For the Rosetta Code problem, then, a solution can be represented using a list of 22 integers of the values 0 or 1. A value of 1 represents picking the corresponding item, while a value of 0 means that the item has not been picked. When applying the genetic algorithms approach, this list of binary values is going to be used as the chromosome.

We have to remember, however, that the total weight of the chosen items cannot exceed the capacity of the knapsack. One way to incorporate this restriction into the solution is to wait until ...