• Class
    This library solves knapsack problems.

    Problems the library solves include:
    - 0-1 knapsack problems,
    - Multi-dimensional knapsack problems,

    Given n items, each with a profit and a weight, given a knapsack of
    capacity c, the goal is to find a subset of items which fits inside c
    and maximizes the total profit.
    The knapsack problem can easily be extended from 1 to d dimensions.
    As an example, this can be useful to constrain the maximum number of
    items inside the knapsack.
    Without loss of generality, profits and weights are assumed to be positive.

    From a mathematical point of view, the multi-dimensional knapsack problem
    can be modeled by d linear constraints:

    ForEach(j:1..d)(Sum(i:1..n)(weight_ij * item_i) <= c_j
    where item_i is a 0-1 integer variable.

    Then the goal is to maximize:

    Sum(i:1..n)(profit_i * item_i).

    There are several ways to solve knapsack problems.
    Enum controlling which underlying algorithm is used.

    This enum is passed to the constructor of the KnapsackSolver object.
    It selects which solving method will be used.