Knapsack-like Problems
If all the profits are 1, we can try to minimize the number of items which exactly fill the knapsack:
minimize | ||
subject to | ||
If we have a number of containers (of the same size), and we wish to pack all n items in as few containers as possible, we get the bin packing problem, which is modelled by having indicator variables container i is being used:
minimize | ||
subject to | ||
The cutting stock problem is identical to the bin packing problem, but since practical instances usually have far fewer types of items, another formulation is often used. Item j is needed Bj times, each "pattern" of items which fit into a single knapsack have a variable, xi (there are m patterns), and pattern i uses item j bij times:
minimize | ||
subject to | for all | |
for all |
If, to the multiple choice knapsack problem, we add the constraint that each subset is of size n and remove the restriction on total weight, we get the assignment problem, which is also the problem of finding a maximal bipartite matching:
maximize | ||
subject to | for all | |
for all | ||
for all and all |
In the Maximum Density Knapsack variant there is an initial weight, and we maximize the density of selected of items which do not violate the capacity constraint:
maximize | ||
subject to | ||
Although less common than those above, several other knapsack-like problems exist, including:
- Nested knapsack problem
- Collapsing knapsack problem
- Nonlinear knapsack problem
- Inverse-parametric knapsack problem
The last three of these are discussed in Kellerer et al's reference work, Knapsack Problems.
Read more about this topic: List Of Knapsack Problems
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