Abstract
The paper gives a method of minimizing a linear function of zero-one variables subject to linear constraints. The method is based on transforming an n-variable m-constraint problem into a sequence of n-variable 2-constraint problems which are easier to solve. The algorithm has been tested on test problems found in the literature and on a set of 80 random problems. Good results have been obtained, both in terms of the number of iterations involved in solving this sequence of subproblems, and in terms of the total computation time required to reach the final solution. The method is most effective when the coefficients of the problem are small integer numbers.
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