We know that the effectiveness of the branch-and-bound algorithms proposed for the solution of combinatorial optimization problems greatly depends on the tightness of the available bounds. In this paper, we consider optimization problems with a linear objective function. We propose an additive approach for computing lower bounds that yields an increasing sequence of values. An application to the traveling salesman problem with precedence constraints is presented to exemplify the technique.
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Fischetti et al. (1989) studied this question.
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