The source code and dockerfile for the GSW2024 AI Lab.
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
This repo is archived. You can view files and clone it, but cannot push or open issues/pull-requests.
 
 
 
 
 
 

111 lines
3.1 KiB

/* min01ks.mod - finding minimal equivalent 0-1 knapsack inequality */
/* Written in GNU MathProg by Andrew Makhorin <mao@gnu.org> */
/* It is obvious that for a given 0-1 knapsack inequality
a[1] x[1] + ... + a[n] x[n] <= b, x[j] in {0, 1} (1)
there exist infinitely many equivalent inequalities with exactly the
same feasible solutions.
Given a[j]'s and b this model allows to find an inequality
alfa[1] x[1] + ... + alfa[n] x[n] <= beta, x[j] in {0, 1}, (2)
which is equivalent to (1) and where alfa[j]'s and beta are smallest
non-negative integers.
This model has the following formulation:
minimize
z = |alfa[1]| + ... + |alfa[n]| + |beta| = (3)
= alfa[1] + ... + alfa[n] + beta
subject to
alfa[1] x[1] + ... + alfa[n] x[n] <= beta (4)
for all x satisfying to (1)
alfa[1] x[1] + ... + alfa[n] x[n] >= beta + 1 (5)
for all x not satisfying to (1)
alfa[1], ..., alfa[n], beta are non-negative integers.
Note that this model has n+1 variables and 2^n constraints.
It is interesting, as noticed in [1] and explained in [2], that
in most cases LP relaxation of the MIP formulation above has integer
optimal solution.
References
1. G.H.Bradley, P.L.Hammer, L.Wolsey, "Coefficient Reduction for
Inequalities in 0-1 Variables", Math.Prog.7 (1974), 263-282.
2. G.J.Koehler, "A Study on Coefficient Reduction of Binary Knapsack
Inequalities", University of Florida, 2001. */
param n, integer, > 0;
/* number of variables in the knapsack inequality */
set N := 1..n;
/* set of knapsack items */
/* all binary n-vectors are numbered by 0, 1, ..., 2^n-1, where vector
0 is 00...00, vector 1 is 00...01, etc. */
set U := 0..2^n-1;
/* set of numbers of all binary n-vectors */
param x{i in U, j in N}, binary, := (i div 2^(j-1)) mod 2;
/* x[i,j] is j-th component of i-th binary n-vector */
param a{j in N}, >= 0;
/* original coefficients */
param b, >= 0;
/* original right-hand side */
set D := setof{i in U: sum{j in N} a[j] * x[i,j] <= b} i;
/* set of numbers of binary n-vectors, which (vectors) are feasible,
i.e. satisfy to the original knapsack inequality (1) */
var alfa{j in N}, integer, >= 0;
/* coefficients to be found */
var beta, integer, >= 0;
/* right-hand side to be found */
minimize z: sum{j in N} alfa[j] + beta; /* (3) */
phi{i in D}: sum{j in N} alfa[j] * x[i,j] <= beta; /* (4) */
psi{i in U diff D}: sum{j in N} alfa[j] * x[i,j] >= beta + 1; /* (5) */
solve;
printf "\nOriginal 0-1 knapsack inequality:\n";
for {j in 1..n} printf (if j = 1 then "" else " + ") & "%g x%d",
a[j], j;
printf " <= %g\n", b;
printf "\nMinimized equivalent inequality:\n";
for {j in 1..n} printf (if j = 1 then "" else " + ") & "%g x%d",
alfa[j], j;
printf " <= %g\n\n", beta;
data;
/* These data correspond to the very first example from [1]. */
param n := 8;
param a := [1]65, [2]64, [3]41, [4]22, [5]13, [6]12, [7]8, [8]2;
param b := 80;
end;