$2$ Part $($b$)$: Bin$-$packing Problem

Note: Most of your code $-$ selection, mutation, crossover, over all structure can

be re$-$used with some minor changes. The main aspects to concentrate on are:

fitness function, representation, analysis of results.

The Bin packing problem on wikipedia gives a high$-$level description of the

bin$-$packing problem. There are many applications of the bin$-$packing problem

and many extensions of the problem that have varied applications. It is a

combinatorial optimisation problem where the goal is to efficiently pack a set of

items into the minimum of bins.

In this question, you are provided with several problem instances $-$ items

weights, bins and their capacity. Your developed GA should be able to tackle

these problems and give a solution.

Typically, you have a set of items each with a weight $($or size or some other

values. The goal is to pack these items into a set of bins each with a fixed

capacity. The goal is to use as few bins as possible to pack the items.

You should submit:

$$ A description of your representation of your solutions

$$ A description of your fitness function and operators together with any

justifications of your choice

$$ Any insights into the problem landscape.