Scilab function

knapsack - solves a 0-1 multiple knapsack problem

### Calling Sequence

  `[earn,ind] = knapsack(profit,weight,capa,[bck])`

### Parameters

- `profit` : integer row vector
- `weight` : integer row vector
- `capa` : integer row vector
- `bck` : integer
- `earn` : integer
- `ind` : integer row vector

### Description

`knapsack` solve a 0-1 multiple knapsack problem with n (n >= 2) items and m knapsacks (m >= 1). `profit` is the vector of the (integer) profits of the n items and `weight` is the vector of the corresponding (integer) weights. `capa` is the vector of the (integer) capacities of the m knapsacks. `bck` is an optional integer: the maximum number of backtrackings to be performed, if heuristic solution is required. If the exact solution is required `bck` can be omitted or can have a negative value. `earn` is the value of the criterium for the "optimal" solution and `ind` is a vector giving the optimal location: `ind(i)` gives the number of the knapsack where item i is inserted and this value is 0 if the item i is not in the optimal solution.

We recall that the problem to be solved is the following: `p(i)` and `w` denote respectively the profit and the weight of the item `i` 1=1,...,n; `c(j)` denotes the capacity of the knapsack `j` j=1,...,m; `q(j,i)` denotes the quantity of item `i` in knapsack `j` (in fact 0 or 1).

We want to maximize the global profit `E` : `E=p(1)*[x(1,1)+...+x(m,1)]+...+p(n)*[x(1,n)+...+x(m,n)]`

under the constraints: `[w(1)*x(j,1)+...+w(n)*x(j,m)] <= c(j) ; j=1,...,m` `[x(1,i)+...+x(m,i)] <= 1 ; i=1,...,n` `x(j,i)= 0 or 1` `p(),w(),c()` are positive integers.

### Examples

    weight=ones(1,15).*.[1:4];
    profit=ones(1,60);
    capa=[15 45 30 60];
    [earn,ind]=knapsack(profit,weight,capa)

### See Also

`qassign` ,