diff -r d59bea55db9b -r c445c931472f examples/bpp.mod --- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/examples/bpp.mod Mon Dec 06 13:09:21 2010 +0100 @@ -0,0 +1,83 @@ +/* BPP, Bin Packing Problem */ + +/* Written in GNU MathProg by Andrew Makhorin */ + +/* Given a set of items I = {1,...,m} with weight w[i] > 0, the Bin + Packing Problem (BPP) is to pack the items into bins of capacity c + in such a way that the number of bins used is minimal. */ + +param m, integer, > 0; +/* number of items */ + +set I := 1..m; +/* set of items */ + +param w{i in 1..m}, > 0; +/* w[i] is weight of item i */ + +param c, > 0; +/* bin capacity */ + +/* We need to estimate an upper bound of the number of bins sufficient + to contain all items. The number of items m can be used, however, it + is not a good idea. To obtain a more suitable estimation an easy + heuristic is used: we put items into a bin while it is possible, and + if the bin is full, we use another bin. The number of bins used in + this way gives us a more appropriate estimation. */ + +param z{i in I, j in 1..m} := +/* z[i,j] = 1 if item i is in bin j, otherwise z[i,j] = 0 */ + + if i = 1 and j = 1 then 1 + /* put item 1 into bin 1 */ + + else if exists{jj in 1..j-1} z[i,jj] then 0 + /* if item i is already in some bin, do not put it into bin j */ + + else if sum{ii in 1..i-1} w[ii] * z[ii,j] + w[i] > c then 0 + /* if item i does not fit into bin j, do not put it into bin j */ + + else 1; + /* otherwise put item i into bin j */ + +check{i in I}: sum{j in 1..m} z[i,j] = 1; +/* each item must be exactly in one bin */ + +check{j in 1..m}: sum{i in I} w[i] * z[i,j] <= c; +/* no bin must be overflowed */ + +param n := sum{j in 1..m} if exists{i in I} z[i,j] then 1; +/* determine the number of bins used by the heuristic; obviously it is + an upper bound of the optimal solution */ + +display n; + +set J := 1..n; +/* set of bins */ + +var x{i in I, j in J}, binary; +/* x[i,j] = 1 means item i is in bin j */ + +var used{j in J}, binary; +/* used[j] = 1 means bin j contains at least one item */ + +s.t. one{i in I}: sum{j in J} x[i,j] = 1; +/* each item must be exactly in one bin */ + +s.t. lim{j in J}: sum{i in I} w[i] * x[i,j] <= c * used[j]; +/* if bin j is used, it must not be overflowed */ + +minimize obj: sum{j in J} used[j]; +/* objective is to minimize the number of bins used */ + +data; + +/* The optimal solution is 3 bins */ + +param m := 6; + +param w := 1 50, 2 60, 3 30, 4 70, 5 50, 6 40; + +param c := 100; + +end;