knapsack - solves a 0-1 multiple knapsack problem
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.
weight=ones(1,15).*.[1:4]; profit=ones(1,60); capa=[15 45 30 60]; [earn,ind]=knapsack(profit,weight,capa)
qassign ,